{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#                                                HW2: Logistic 回归&SVM\n",
    "\n",
    "1、 任务描述\n",
    "请在 Pima Indians Diabetes Data Set（皮马印第安人糖尿病数据集）进行分类器练习。\n",
    "\n",
    "需要提交代码文件，并给出必要的结果解释。\n",
    "1) 训练数据和测试数据分割（随机选择 20%的数据作为测试集）；（10 分）\n",
    "\n",
    "2) 适当的特征工程（及数据探索）;（10 分）\n",
    "\n",
    "3) Logistic 回归，并选择最佳的正则函数（L1/L2）及正则参数； （30 分）\n",
    "\n",
    "4) 线性 SVM，并选择最佳正则参数，比较与 Logistic 回归的性能，简单说明原因。（20 分）\n",
    "\n",
    "5) RBF 核的 SVM，并选择最佳的超参数（正则参数、 RBF 核函数宽度） ；（30 分）\n",
    "\n",
    "数据集只有一个文件（diabetes.csv）：Pima Indians Diabetes Dataset 包括根据医疗记录的比马印第安人 5 年内糖尿病的发病情况，这是一个两类分类问题。每个类的样本数目数量不均等。一共有 768 个样本，每个样本有 8 个输入变量和 1 个输出变量。缺失值通常用零值编码。\n",
    "\n",
    "\n",
    "\n",
    "下面为字段说明:\n",
    "\n",
    "Pregnancies： 怀孕次数\n",
    "\n",
    "Glucose： 口服葡萄糖耐受试验中，2 小时的血浆葡萄糖浓度。\n",
    "\n",
    "BloodPressure： 舒张压（mm Hg）\n",
    "\n",
    "SkinThickness： 三头肌皮肤褶层厚度（mm）\n",
    "\n",
    "Insulin：2 小时血清胰岛素含量（μU/ ml）\n",
    "\n",
    "BMI： 体重指数（体重，kg /（身高，m）^ 2）\n",
    "\n",
    "DiabetesPedigreeFunction： 糖尿病家族史\n",
    "\n",
    "Age： 年龄（岁）\n",
    "\n",
    "Outcome： 输出变了/类别标签（0 或 1，出现糖尿病为 1, 否则为 0）"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1  导入相应的包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 首先 import 必要的模块\n",
    "import pandas as pd \n",
    "import numpy as np\n",
    "# 载入库包\n",
    "from sklearn.linear_model import LogisticRegression  \n",
    "from sklearn.model_selection import GridSearchCV  \n",
    "from sklearn.metrics import classification_report \n",
    "\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "#竞赛的评价指标为logloss\n",
    "from sklearn.metrics import log_loss  \n",
    "from sklearn import metrics\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. 定义函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 定义单变量画直方图和散点图的函数\n",
    "def drawHisAndScatter(dFrame,name):\n",
    "    fig=plt.figure(figsize=(10,5))\n",
    "    sns.distplot(dFrame[name].values, bins=30, kde=True)\n",
    "    plt.title(\"Histogram of \"+name);\n",
    "    plt.xlabel('Value of '+name, fontsize=12)\n",
    "    plt.ylabel('Probability', fontsize=12)\n",
    "    plt.show()\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. 读取数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pregnancies</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>BloodPressure</th>\n",
       "      <th>SkinThickness</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>DiabetesPedigreeFunction</th>\n",
       "      <th>Age</th>\n",
       "      <th>Outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>148</td>\n",
       "      <td>72</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>33.6</td>\n",
       "      <td>0.627</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>85</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>26.6</td>\n",
       "      <td>0.351</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>183</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>0.672</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>89</td>\n",
       "      <td>66</td>\n",
       "      <td>23</td>\n",
       "      <td>94</td>\n",
       "      <td>28.1</td>\n",
       "      <td>0.167</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>40</td>\n",
       "      <td>35</td>\n",
       "      <td>168</td>\n",
       "      <td>43.1</td>\n",
       "      <td>2.288</td>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Pregnancies  Glucose  BloodPressure  SkinThickness  Insulin   BMI  \\\n",
       "0            6      148             72             35        0  33.6   \n",
       "1            1       85             66             29        0  26.6   \n",
       "2            8      183             64              0        0  23.3   \n",
       "3            1       89             66             23       94  28.1   \n",
       "4            0      137             40             35      168  43.1   \n",
       "\n",
       "   DiabetesPedigreeFunction  Age  Outcome  \n",
       "0                     0.627   50        1  \n",
       "1                     0.351   31        0  \n",
       "2                     0.672   32        1  \n",
       "3                     0.167   21        0  \n",
       "4                     2.288   33        1  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 读取数据\n",
    "# path to where the data lies\n",
    "dpath = './data/'\n",
    "train = pd.read_csv(\"diabetes.csv\")\n",
    "train.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. 数据探索"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 768 entries, 0 to 767\n",
      "Data columns (total 9 columns):\n",
      "Pregnancies                 768 non-null int64\n",
      "Glucose                     768 non-null int64\n",
      "BloodPressure               768 non-null int64\n",
      "SkinThickness               768 non-null int64\n",
      "Insulin                     768 non-null int64\n",
      "BMI                         768 non-null float64\n",
      "DiabetesPedigreeFunction    768 non-null float64\n",
      "Age                         768 non-null int64\n",
      "Outcome                     768 non-null int64\n",
      "dtypes: float64(2), int64(7)\n",
      "memory usage: 54.1 KB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "通过 info 方法可以看到样本数为768个，8个特征值，一个类别判断目标值。 数据中 BMI 和 DiabetesPedigreeFunction 为浮点数，其余数据都为整数。由说明可得 糖尿病家族史应该处理为了一个倍数问题，整体数值都不大。BMI就是我们常见的身高体重的指标，这两个允许浮点数。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pregnancies</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>BloodPressure</th>\n",
       "      <th>SkinThickness</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>DiabetesPedigreeFunction</th>\n",
       "      <th>Age</th>\n",
       "      <th>Outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.845052</td>\n",
       "      <td>120.894531</td>\n",
       "      <td>69.105469</td>\n",
       "      <td>20.536458</td>\n",
       "      <td>79.799479</td>\n",
       "      <td>31.992578</td>\n",
       "      <td>0.471876</td>\n",
       "      <td>33.240885</td>\n",
       "      <td>0.348958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.369578</td>\n",
       "      <td>31.972618</td>\n",
       "      <td>19.355807</td>\n",
       "      <td>15.952218</td>\n",
       "      <td>115.244002</td>\n",
       "      <td>7.884160</td>\n",
       "      <td>0.331329</td>\n",
       "      <td>11.760232</td>\n",
       "      <td>0.476951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.078000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>27.300000</td>\n",
       "      <td>0.243750</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>30.500000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>0.372500</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>140.250000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>127.250000</td>\n",
       "      <td>36.600000</td>\n",
       "      <td>0.626250</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>17.000000</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>122.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>846.000000</td>\n",
       "      <td>67.100000</td>\n",
       "      <td>2.420000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Pregnancies     Glucose  BloodPressure  SkinThickness     Insulin  \\\n",
       "count   768.000000  768.000000     768.000000     768.000000  768.000000   \n",
       "mean      3.845052  120.894531      69.105469      20.536458   79.799479   \n",
       "std       3.369578   31.972618      19.355807      15.952218  115.244002   \n",
       "min       0.000000    0.000000       0.000000       0.000000    0.000000   \n",
       "25%       1.000000   99.000000      62.000000       0.000000    0.000000   \n",
       "50%       3.000000  117.000000      72.000000      23.000000   30.500000   \n",
       "75%       6.000000  140.250000      80.000000      32.000000  127.250000   \n",
       "max      17.000000  199.000000     122.000000      99.000000  846.000000   \n",
       "\n",
       "              BMI  DiabetesPedigreeFunction         Age     Outcome  \n",
       "count  768.000000                768.000000  768.000000  768.000000  \n",
       "mean    31.992578                  0.471876   33.240885    0.348958  \n",
       "std      7.884160                  0.331329   11.760232    0.476951  \n",
       "min      0.000000                  0.078000   21.000000    0.000000  \n",
       "25%     27.300000                  0.243750   24.000000    0.000000  \n",
       "50%     32.000000                  0.372500   29.000000    0.000000  \n",
       "75%     36.600000                  0.626250   41.000000    1.000000  \n",
       "max     67.100000                  2.420000   81.000000    1.000000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 各属性的统计特性\n",
    "train.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Insulin ,SkinThickness方差较大，波动较大。这可能与缺失值填补0有关系。之后会处理"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. 特征工程"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.1 目标值分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xcbf7b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Target 分布，看看各类样本分布是否均衡\n",
    "sns.set()\n",
    "sns.countplot(train.Outcome);\n",
    "plt.xlabel('Outcome');\n",
    "plt.ylabel('Number of occurrences');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由图可以看出，输出是不是糖药病的样本不均衡，不是糖药病的人比是糖药病的人多200多个，在之后的使用模型训练的时候要注意。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.2 缺失值处理"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于本作业把缺失值都编码为0，但是经过观察发现 Insulin,Glucose,BloodPressure,SkinThickness,BMI 这几个值编码为0显然是不正确的，正常人都会有这几个指标。 Pregnancies 未怀孕次数，无法辨别是0值是不是缺失值，不进行处理。\n",
    "我们按是糖药病的人和不是糖药病的人进行分类。按照两个类别分别计算以上几个指标的平均值。然后对这些特征值的缺失值按照平均值进行填补。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda\\lib\\site-packages\\pandas\\core\\frame.py:2540: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self[k1] = value[k2]\n",
      "C:\\Anaconda\\lib\\site-packages\\ipykernel_launcher.py:19: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "C:\\Anaconda\\lib\\site-packages\\ipykernel_launcher.py:22: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Pregnancies                 0\n",
       "Glucose                     0\n",
       "BloodPressure               0\n",
       "SkinThickness               0\n",
       "Insulin                     0\n",
       "BMI                         0\n",
       "DiabetesPedigreeFunction    0\n",
       "Age                         0\n",
       "Outcome                     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 需要进行对0异常值做处理的特征\n",
    "zeroFields = ['Insulin',  'Glucose', 'BloodPressure', 'SkinThickness','BMI']\n",
    "trainFillOne = train[train[\"Outcome\"] == 1]\n",
    "trainFillZero = train[train[\"Outcome\"] == 0]\n",
    "\n",
    "# 建立是不是糖药病的人的两个字典存储平均值\n",
    "zeroDic = {}\n",
    "oneDic = {}\n",
    "for index in zeroFields:\n",
    "     zeroDic[index]=trainFillZero[index].sum()/len(trainFillZero.loc[trainFillZero[index] >0]);\n",
    "     oneDic[index]=trainFillOne[index].sum()/len(trainFillOne.loc[trainFillOne[index] >0]);\n",
    "\n",
    "# 对0值的缺失值进行转换为NA\n",
    "trainFillOne[zeroFields] =trainFillOne[zeroFields].where(trainFillOne[zeroFields]>0)    \n",
    "trainFillZero[zeroFields] = trainFillZero[zeroFields].where(trainFillZero[zeroFields] >0)\n",
    "\n",
    "# 进行填补\n",
    "for key,val in zeroDic.items():\n",
    "    trainFillZero[key]=trainFillZero[key].fillna(val)\n",
    "\n",
    "for key,val in oneDic.items():\n",
    "    trainFillOne[key]=trainFillOne[key].fillna(val)    \n",
    "\n",
    "# 填不完后，把两个dataFrame进行结合，并打乱顺序\n",
    "trainFilled = trainFillZero.append(trainFillOne)\n",
    "trainFilled = trainFilled.sample(frac = 1)\n",
    "trainFilled.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.3 单值特征值分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xcbf93c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd029dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xcfc7780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xcff25f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xcd8d630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xefa0c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAl8AAAFKCAYAAAAjTDqoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzs3Xd4VFX+P/D3nT6TmVTSSEiA0JQWQkcCAi5YQKQjLuiiLvqFdWUXy0/FVUFRRL8qLoL6fdhdbCCoK+u6ghR1UTqBUEIngUB6m5JMu+f3R8hABEKATM379Tx5yNw7M/czJ0PmnXPOPVcSQggQERERkU8o/F0AERERUXPC8EVERETkQwxfRERERD7E8EVERETkQwxfRERERD7E8EVERETkQwxfRF7UsWNHlJWV1dv2xRdfYMaMGQCAt99+G1999VWDz/Huu+/i+++/91qN3nTo0CHcdtttGDt2LM6cOVNv39ChQzFixAiMHj0ad999N0aNGoX33nsPLpcLALBhwwbMnz+/wec/c+YMevTocc11bd68GW+//fY1P67O4sWL0a9fP4wePRr33HMPRo0ahQceeAAnT568pucpKytDx44dATTu9TaVL774Aj179sTo0aPrfW3YsKHJj3Xx+7cx73ei5kDl7wKImrM//vGPV73Ptm3b0K5dOx9U0/Q2bNiAvn374uWXX77s/kWLFqFr164AAJvNhjlz5mDBggWYO3cuhg0bhmHDhnmlruzsbFRWVt7Qc9x55514/vnnPbdXrFiBP//5z/jiiy+u6/m8+Xovp1evXli2bJnXj3Px+7cx73ei5oDhi8iPnn76abRv3x4PPvgg3nnnHaxfvx5qtRpRUVFYsGAB1q9fj/3792PhwoVQKpXo168fXnzxReTk5ECSJGRmZuJPf/oTVCoVfvjhByxatAgKhQI33XQTfv75Z3zyySfYvn07Vq9ejerqahiNRixbtgwvvPACcnNzUVFRgbCwMCxatAht27bF1KlT0blzZ2RlZaGsrAwTJ05ESUkJtm/fjurqarz11luenpqL/fWvf8U333wDpVKJNm3aYO7cufjll1/w6aefwu12o6amBm+88UaDbWEwGPD888/jtttuw+zZs7Fu3Tp89913WLZsGbKysvD666/D4XCguLgYAwYMwCuvvAIAkGUZzz77LA4cOACVSoXnnnsO6enpAID33nsP69atgyzLSEpKwl/+8hcUFBTgs88+g9vthslkwuzZs/H555/j008/hSzLiIyMxNy5c5GWloadO3fi1VdfhSzLAIAZM2ZgxIgRl62/f//+ePPNNwEAZrMZL7/8Mo4cOQKn04n+/fvjySefhEqlwrp16/C///u/0Ov16NKli+fxX3zxhef15ubm4plnnkFlZSViY2MhhMDdd9+NPn364L777kNaWhry8/OxYsUKnDlzBosWLUJ1dTUUCgVmzZqFIUOGAMAVX1dDLq7j17effvppGI1GHD58GAUFBejYsSNee+01hIWFYe/evZg/fz6qq6uhVqvx5JNP4sSJE/Xevxs2bPC833fu3ImFCxd67v/4449j0KBB+OKLL7B+/XooFArk5uZCp9Phtddeu2rdREFFEJHXdOjQQYwcOVLcfffdnq/BgweL3//+90IIIZ566inx4YcfirNnz4qMjAxht9uFEEL83//9n1i/fr0QQojf/va34ttvvxVCCPHkk0+KefPmCVmWhd1uF9OnTxfLli0TZWVlok+fPuLQoUNCCCG++OIL0aFDB3H69GmxZs0a0bt3b2E2m4UQQnz77bdi3rx5nhrnzp0rXnrpJc+xZs2aJYQQIisrS3To0EFs2LBBCCHEyy+/LJ577rlLXuPq1avFpEmThNVqFUII8c4774jp06d7vn/xxRcv2zZDhgwR+/btu2R73759xd69e8WaNWs87TR79myxdetWIYQQFotF9O3bV2RnZ4vTp0+LDh06iG+++UYIIcRPP/0kBg0aJOx2u/jyyy/F448/LpxOpxBCiM8++0w89NBDl9S1bds2MWXKFGGz2TzPcfvttwshhJg2bZr417/+JYQQ4tChQ+KFF1647OtyOp1iwYIFYsaMGUIIIZ5++mnxj3/8QwghhMvlEnPmzBHvv/++KC4uFj179hRHjx4VQgixdOlS0aFDByGEqPd6J06cKD7++GMhhBDHjh0T3bt3F2vWrPG83h07dgghhKioqBDDhw8Xp0+fFkIIUVBQIAYNGiTy8/MbfF1r1qwRGRkZ9d6Xc+fOvaSOX99+6qmnxKRJk4TdbhcOh0Pcc889YvXq1cLhcIhbbrlFbNq0SQghRHZ2thg5cqRwu9313r917/eysjLRv39/kZWVJYQQ4siRI6JPnz4iLy9PrFmzRvTs2VOcO3dOCCHESy+9JJ588snLvoeIghV7voi87O9//zuio6M9t+t6Ei4WHx+PTp06YcyYMRg0aBAGDRqE/v37X/JcP/74Iz799FNIkgSNRoPJkyfj73//O9q0aYO0tDR06tQJADBmzJh684c6duwIo9EIALj99tvRqlUrrFixArm5udi+fXu9eVO/+c1vAACtWrUCAGRmZgIAUlJSsH379svWNHbsWBgMBgDAtGnTsHTpUjgcjmtvLACSJEGv19fb9uqrr+LHH3/E0qVLceLECdjtdthsNkRGRiI8PBx33nknAGDgwIEAgBMnTmDTpk3Izs7GuHHjANT2kFVXV19yvM2bNyM3NxeTJ0/2bKuqqkJFRQXuuOMOvPTSS9i4cSMGDBiAP/3pT577/Pvf/8auXbsAAE6nE507d8a8efM8z5mdnY3Vq1cDAGpqagAAu3btQocOHTzDcJMmTfL0ltWprKzEvn378NFHHwEA0tLS0K9fP89+lUrl6dnLyspCcXExZs6cWa/9Dh8+jB07dlzxdQHXP+yYmZkJjUYDAOjQoQMqKytx5MgRKBQK3HrrrQCALl26YO3atVd8jn379iElJQXdu3cHALRv3x4ZGRnYvn07JElC586dkZCQAAC4+eabsX79+muukyiQMXwRBQCFQoGPPvoI2dnZ+OWXX/DKK68gMzMTTz75ZL37ybIMSZLq3Xa5XFAqlRC/ukyrQnHhfJq6YAQAn3zyCVatWoX77rsPo0aNQmRkZL3J8HUfrHXUanWDtV+ppuuRn58Pm82GlJQUZGdne7b/9re/RceOHZGZmYk77rgDe/fu9bzei19n3fHVajVkWcZDDz2EKVOmAAAcDsdl53nJsozRo0fjiSee8NwuKipCREQEJk+ejCFDhmDLli346aef8O677+I///kPgEvnfP36Od9++23PUFlVVRUkScLPP/9c7+ekUl36K1ipVAJAvfvVbQNqfz51j3O73UhLS8Pnn3/u2V9YWIjo6Ghs27btiq+rIZIk1Tu20+mst1+n011yX6VSWe89AABHjhxB27ZtL3sMt9t9yf2FEHC5XFCr1Zc9BlEo4dmORAEgJycHI0eORFpaGmbMmIEHHnjAEz6USqUnzAwcOBAfffQRhBBwOBxYtWoVBgwYgIyMDJw6dQo5OTkAgO+++87zgf9r//3vfzFmzBhMmDABbdq0wcaNG+F2u6+79szMTKxZswY2mw1A7cTz3r17XxLirqaqqgrz5s3DfffdB61WW297dnY25syZg+HDh6OgoAB5eXmeeVgVFRXYtGkTAGDjxo3Q6XRITU3FwIEDsXr1algsFgC1Z9rVhdlft+k333yDoqIiAMCnn36K+++/HwAwefJkHDp0CGPHjsW8efNQVVWF4uLiq76WgQMH4m9/+5vn5/Too4/io48+Qu/evXHs2DHPz+lyk/ONRiMyMjI8+06fPo1ffvnlsj/L9PR05ObmYseOHQBqzy4dMWIECgsLG3xdDYmOjsbRo0dht9vhdDov6aW9nLZt20KSJGzZsgUAcODAAdx///2QZbleW19c94kTJ7Bv3z4AwNGjR7Fjxw706dPnqsciCgXs+SIKAJ06dcIdd9yBcePGwWAwQKfT4bnnngNQuyTDm2++CafTieeeew7z58/HqFGj4HQ6kZmZiUceeQQajQZvvvkmnnrqKSgUCnTp0gUqleqS4TsAmD59Op5//nnPkFh6ejqOHDly3bWPHz8e586dw4QJEyDLMlJTU7Fo0aJGPXbOnDnQ6XRQKpVwu90YPnw4HnnkkXr3CQ8Px+9//3uMGTMGBoMB8fHxyMjIQG5uLlq1aoWYmBisW7cOb731FvR6PRYvXgyVSoUJEyagsLAQEydOhCRJSExMxKuvvgoA6NevH+bMmYN58+Zh7ty5ePjhhzF9+nRIkgSj0Yh3330XkiRhzpw5eOWVV/DWW29BkiTMmjULycnJV31dzz77LF5++WXPz2nAgAF46KGHoFarsWjRIsyZMwdqtRq9e/e+7ONfe+01PPvss/jkk08QHx+P5OTker1BdaKjo/HOO+9g4cKFsNvtEEJg4cKFSE5ORnJy8hVfV0NuueUW9O7dG3fccQdiY2PRt29fHD58uMHHaDQaLF68GK+88goWLlwItVqNxYsXQ6PR1Hv/Xlz322+/jXnz5qGmpgaSJGHBggVo06YN9uzZc9X2JQp2kmB/LlHQs1gsWLJkCf7whz9Ar9fjwIEDmDFjBn766aerfthS4HnvvfcwfPhwpKWlwWw24+6778YHH3wQtEuOEFF97PkiCgFGoxFqtRrjx4+HSqWCSqXy9NZQ8GndujVmz54NhUIBt9uNhx9+mMGLKISw54uIiIjIhzjhnoiIiMiHGL6IiIiIfIjhi4iIiMiHgmbCfXGx2d8leEVUlAHl5TZ/lxHy2M6+wXb2Dbazb7CdfSNU2zk21nTFfez58jOVSnn1O9ENYzv7BtvZN9jOvsF29o3m2M4MX0REREQ+5LVhR6fTiWeeeQb5+fmey2sMGzbMs3/58uVYvXq154LDL7744hWvA0ZEREQUKrwWvr7++mtERkbi9ddfR3l5OcaMGVMvfB04cACvvfYaunTp4q0SiIiIiAKO18LX7bffjhEjRnhuK5X1x3QPHDiA999/H8XFxbj11lsxY8YMb5VCREREFDC8vsK9xWLBo48+iokTJ2LUqFGe7e+++y6mTJkCo9GIWbNm4d5778WQIUOu+Dwul7tZTsojIiKi0OLV8HXu3DnMnDkTU6ZMwfjx4z3bhRCwWCwwmWpPw/z4449RUVGBmTNnXvG5QnWpidhYU8i+tkDCdvYNtrNvsJ19g+3sG6Hazn5ZaqKkpATTp0/HE088US94AbW9YSNHjoTVaoUQAtu2bePcLyIiImoWvDbna+nSpaiqqsKSJUuwZMkSAMCECRNQXV2NSZMmYfbs2Zg2bRo0Gg369++PwYMHe6sUIiIiooDh9TlfTSUUuySB0O1uDTRsZ99gO/sG29k32M6+EartzBXuiYiIiAIEwxcRERGRDwXNhbXJ/zZn5V/X425NT2riSoiIiIIXe76IiIiIfIjhi4iIiMiHGL6IiIiIfIjhi4iIiMiHGL6IiIiIfIjhi4iIiMiHGL6IiIiIfIjhi4iIiMiHGL6IiIiIfIjhi4iIiMiHGL6IiIiIfIjhi4iIiMiHGL6IiIiIfIjhi4iIiMiHGL6IiIiIfIjhi4iIiMiHGL6IiIiIfIjhi4iIiMiHGL6IiIiIfIjhi4iIiMiHGL6IiIiIfIjhi4iIiMiHGL6IiIiIfIjhi4iIiMiHGL6IiIiIfIjhi4iIiMiHGL6IiIiIfIjhi4iIiMiHGL6IiIiIfIjhi4iIiMiHGL6IiIiIfIjhi4iIiMiHGL6IiIiIfIjhi4iIiMiHGL6IiIiIfIjhi4iIiMiHGL6IiIiIfIjhi4iIiMiHGL6IiIiIfIjhi4iIiMiHGL6IiIiIfIjhi4iIiMiHVN56YqfTiWeeeQb5+flwOBx49NFHMWzYMM/+jRs34q9//StUKhXGjRuHiRMneqsUIiIiooDhtfD19ddfIzIyEq+//jrKy8sxZswYT/hyOp1YsGABVq9eDb1ej3vvvRdDhgxBbGyst8ohIiIiCgheG3a8/fbb8cc//tFzW6lUer4/fvw4UlJSEBERAY1Gg549e2Lnzp3eKoWIiIgoYHit5yssLAwAYLFY8Nhjj+Hxxx/37LNYLDCZTPXua7FYGny+qCgDVCplg/cJVrGxpqvfKQCYjLrrelygvL5AqSPUsZ19g+3sG2xn32hu7ey18AUA586dw8yZMzFlyhSMGjXKs91oNMJqtXpuW63WemHscsrLbV6r059iY00oLjb7u4xGMVtqrutxgfD6gqmdgxnb2TfYzr7BdvaNUG3nhgKl14YdS0pKMH36dDzxxBMYP358vX1paWnIzc1FRUUFHA4Hdu7ciR49enirFCIiIqKA4bWer6VLl6KqqgpLlizBkiVLAAATJkxAdXU1Jk2ahKeffhoPPvgghBAYN24c4uPjvVUKERERUcCQhBDC30U0Rih2SQLB1d26OSv/uh53a3pSE1dy7YKpnYMZ29k32M6+wXb2jVBtZ78MOxIRERHRpRi+iIiIiHyI4YuIiIjIhxi+iIiIiHyI4YuIiIjIhxi+iIiIiHyI4YuIiIjIhxi+6LrIQsDudPu7DCIioqDj1Ws7UugQQuBsiRVF5dUorqhGSWUNXG4Zt3RNQNuWEf4uj4iIKGgwfFGjfL7pOL7fecZzO9ygRrUD2LKvAAqFAq0TmtcV6YmIiK4XwxddVW6BGd/tyIPJoEbvTnFoEamHTqNESUU11u84g5/2noVSkYRWcUZ/l0pERBTwOOeLGiTLAv/47jCEAPreHI/kOCN0GiUAoEWkHkN7JUGpkPDDnrM4W2L1c7VERESBj+GLGvTD3rM4ea4KfW+OR8sWYZfsj48yYEhGEiABm3bno9Ji90OVREREwYPhi66o0urA6s3HodcqMXlouyveLzEmDLd0SYBbFth3vNSHFRIREQUfhi+6opUbj6La7sLYQWmIMGobvG/rRBOiTFqcOmdGldXhowqJiIiCD8MXXVZObjm2HihE6wQThvRIuur9JUlCt7QYCADZ7P0iIiK6Ip7t2Mxszspv1P1+yDoLALgpNQo/7jvbqMekxBsRYdTgxLkqdGsXA5NBc911EhERhSr2fNElnC4Z+cUWmAxqtIjUNfpxnt4vAWSfKPNihURERMGL4YsukV9ihcst0DrBBEmSrumxqQkmhIdpcDy/EpZqp5cqJCIiCl4MX3SJ3AIzgNogda0UkoSubaMhBLD/BOd+ERER/RrDF9XjdMk4U2RBuEGNKFPDZzheSZvEcJgMahw7UwlbDXu/iIiILsbwRfXkl1jhlgVSr2PIsY5CIeHm1tGQBXA8v6qJKyQiIgpuDF9UT+652rDUOvHGLpTdJtEEhULC8fxKCCGaojQiIqKQwPBFHk6XjDPFVoQb1Ii8yqKqV6NRK5ESZ0SVzYkT59j7RUREVIfhizzyiy21Q46J4dc95HixtKRwAMDP2QU3/FxEREShguGLPOrOcmydYGyS50uMCYNeq8T2Q4VwuuQmeU4iIqJgx/BFAC4acgzT3PCQYx2FQkKbxHBYa1zYe6ykSZ6TiIgo2DF8EYCLhhxv4CzHy0lLigAAbMk+12TPSUREFMwYvggAcLbUBgBIiWuaIcc6USYtUuNNyD5Rhkqro0mfm4iIKBgxfBEAoKjMBrVSgajwphlyvNiArgmQhcC2A5x4T0RExPBFqLa7UGVzIjZKB0UTDjnW6XtzPJQKCVv2M3wRERExfBGKyqsBAHFRBq88f7hBg25pMThdZMHpIotXjkFERBQsGL7IE77io/ReO0a/zgkAgB05hV47BhERUTBg+CIUldugkCS0iNB57Rjd2sZAo1JgR04xLzdERETNGsNXM+d0ySirsiMmQgel0ntvB61GiW5pMSgss+FMsdVrxyEiIgp0DF/NXHFFNQS8O+RYp1enOADAjpwirx+LiIgoUDF8NXOFdZPto70fvrqntYBGpcDOnCIOPRIRUbPF8NXMFZXVLq4aF+n98KXVKNE1LQYFZTbkl3DokYiImieGr2bMLcsoqaxBlEkLjVrpk2P2Pj/0uJNDj0RE1EwxfDVjpZV2uGWBOB/M96rTLS0GapWC876IiKjZYvhqxorKzw85+jB86TQqdGsbg3OlNuQXc8FVIiJqfhi+mrFCz+Kq3lnZ/kp41iMRETVnDF/NlBACxeXVMOrVMOhUPj1293a1Q487Dxf79LhERESBgOGrmaqw2OFwyT5Z3+vXdBoVuraNwdkSK896JCKiZofhq5ny5fpel9OrUywAnvVIRETNj1fD1969ezF16tRLti9fvhx33XUXpk6diqlTp+LEiRPeLIMuo7SyBgAQG+Gf8NU9rQVUSgXDFxERNTuNmuyzceNGDBkyBJIkNfqJP/jgA3z99dfQ6y/9cD9w4ABee+01dOnSpfGVUpMqq7JDqZAQbtT45fh6rQpd20Zjz9ESnC2xomWLML/UQURE5GuN6vlasWIFhg0bhiVLlqC4uHGTpFNSUrB48eLL7jtw4ADef/993HvvvVi2bFnjq6Um4XbLqLDYER2uheIaAnVT68UFV4mIqBlqVM/X8uXLkZeXh1WrVmHixIno1q0bJk+ejP79+1/xMSNGjMCZM2cuu++uu+7ClClTYDQaMWvWLGzatAlDhgxpsIaoKANUKt+swu5rsbEmnx3LZNShqMwGIYCEmDCYjDqvH/NKr++2fjr87dsc7DlWggfHdPNbHdS02M6+wXb2DbazbzS3dm70GgMpKSmYPXs2unbtioULF+JPf/oTWrRogZdffhndujX+g1MIgfvvvx8mU21DDx48GAcPHrxq+Co/vyBoqImNNaG42Oyz45ktNThdWAUAMOrVMFtqvH7Mhl5f59bRyDpWgn05BUiM8d7Qo6/bubliO/sG29k32M6+Eart3FCgbNSwY25uLl5//XUMHjwYq1atwjPPPIMtW7bgpZdewuOPP35NxVgsFowcORJWqxVCCGzbto1zv3ysrKo2cMWEa/1cyYVrPXLBVSIiai4a1fM1YcIEjBkzBh999BFat27t2d6jRw/06dOnUQdau3YtbDYbJk2ahNmzZ2PatGnQaDTo378/Bg8efF3F0/UprbJDIUmIMPo/fHVv1wIqpYSdOUW4+5Y2/i6HiIjI6xoVvubOnYtRo0bV2/bVV1/hnnvuwauvvnrFxyUnJ2PVqlUAUO/x99xzD+65557rqZdukCwLlJvtiDJpoFT4b7J9HYNOhS5tYpB1rATnSq1eHXokIiIKBA2Gr40bN8LlcuHtt9+GTqeDEAIA4HK5sHjxYgaoIFRptUOWBaLDvT/RvrF6dYpF1rES7Mwpwij2fhERUYhrMHwdOnQIW7duRWlpKf7xj39ceJBKhQceeMDbtZEXlFbaASCgwld6u1iolDnYkVPM8EVERCGvwfA1c+ZMzJw5Ex9//DHuu+8+X9VEXlQaQJPt6xh0KnRuHY29x0s59EhERCGvwfD1z3/+E6NHj4bdbsfy5csv2f+73/3Oa4WRd5RV1UCSgEhT4IQvAOhzUzz2Hi/FtoOFuCezrb/LISIi8poGw1dubi4A4OjRoz4phryrbrJ9RJgGKmVgXVO9R4cW0KgU2HqwEKMHtrmmS1kREREFkwbD12OPPQYAWLBggU+KIe8qKLPB5RaICaD5XnV0GhXS27fA9kNFOHnOjLYtw/1dEhERkVc0GL5+vbzEr61du7ZJiyHvyi2sXUE4kCbbX6xf5wRsP1SErQcLGL6IiChkNRi+5s6d66s6yAdyC86Hr4jAmu9Vp0ubaBj1amw/VIRJQ9tBqQisoVEiIqKm0OCnW0xMDPr06YOwsLDLflFwyavr+TIFZs+XSqlA705xqLI6cCi33N/lEBEReUWDPV8LFy7EsmXL8Ic//OGSfZIkYcOGDV4rjJqWLARyC80ID9NArQrcHqW+N8dj0558bDtQiC5tYvxdDhERUZNrMHwtW7YMQO1K9xTcSiqqUW13Iz7a4O9SGtQuOQIx4TrsOlKMqU43NGqlv0siIiJqUo26tqPNZsN7772HLVu2QK1WY9CgQXj44Yeh0Wi8XR81kdxCCwD45UzHzVn513T/xBYG7D9RhqxjJehzU7yXqiIiIvKPRo0/vfjiiygoKMATTzyBP/7xjzh69Cjmz5/v7dqoCdXN94oKsMVVL6dtYu2ZjtsOFvq5EiIioqbXqJ6vgwcP1ltWom/fvhg9erTXiqKml19sBRAc4SvSpEWUSYt9x0thqXbCqFf7uyQiIqIm06ier4iICFRUVHhu22w2mEwmrxVFTe9MsQXhBjX02kblbb9r2zIcbllg64ECf5dCRETUpBr8JK4bWlSpVBg7diyGDx8OhUKBjRs3ol27dj4pkG5ctd2Fksoa3JQa5e9SGq1ty3BkHS3BD1lnMaxnMi83REREIaPB8BUZGQkA6NWrF3r16uXZPnLkSO9WRU3qbEntkGNSbPCszabXqtCzYyy2HyrC8fwqtEuO8HdJRERETaLB8DVr1qwr7rPZbE1eDHnHmeLaMx2TY42QhfBzNY03uHtLbD9UhB+y8hm+iIgoZDRqAtD333+Pd955BzabDUIIyLKMiooK7Nmzx9v1URM4c36yfXKsEXlFZj9X03gdU6MQF6XH9pwiTL6tPcJ0nHhPRETBr1ET7hcuXIhHHnkEiYmJ+Mtf/oLMzExMnjzZ27VRE8k/3/OV1CJ4hh0BQCFJGNy9JZwuGb/s58R7IiIKDY0KX3q9HnfeeSfS09Oh1WrxwgsvYPPmzV4ujZqCEAJniq2IjdRBqwm+1eJv6ZoIpULCD3vPQgTRkCkREdGVNCp8abVaOBwOpKSk4NChQ1AoFDz7LEhUWR2wVDuRHGv0dynXJTxMg4wOscgvtuL42Sp/l0NERHTDGhW+hg4dit///vcYNGgQ/va3v+EPf/gDoqKCZ9mC5qxuvldSkIYvABic3hIA8MOea7tMERERUSBq1IT7Rx55BHfffTfi4+OxZMkS7Nixg8tNBIkLZzoG13yvi3XixHsiIgohjer5AoDjx4/jtddew7fffoubbroJMTEx3qyLmkh+CPR8KSQJt6YnwemSsZm9X0REFOQaFb56fo36AAAgAElEQVSWLl2KBQsWQKfTQaFQYO7cufj444+9XRs1gTPFFqiUEuKj9P4u5YYM6t4Seq0S63eegcPp9nc5RERE161Rw47/+te/sGrVKhiNtb0n06dPx5QpU3Dfffd5tTi6MbIscLbEisSYMKiUje7kDEgGnQpDeiTj31tzsWV/AYb0SPJ3SURERNelUeFLq9UiLOzCnKGIiAhotVqvFUVNo7iyGg6XHLTzvTZn1R9iDNOroFBI+OqnExAQUFzhjNtb0xnMiIgocDUYvtatWwcAaNOmDf7nf/4HEyZMgFKpxFdffYUuXbr4pEC6fmeKgn++18X0WhXaJYXjyOlK5BWY0Tox3N8lERERXbMGw9eKFSvq3V6+fLnn+9LSUu9URE0mPwTOdPy1m1tH4+jpSuw/WYbUBBPXmyMioqBzTeHL5XJBCAG1mqf6B4OLL6gdKsLDNEhJMCG3wIxzpTa0DLJLJhERETVqFnZpaSkeeughpKeno1u3bpg2bRoKCwu9XRvdoPwSK/RaFaJMoTU/r0ubaADA/hNlfq6EiIjo2jUqfL300ktIT0/Hzz//jJ9//hm9evXCCy+84OXS6EY4XW4UllUjKTYs5IbmYiJ0SIwxoKDMhqJym7/LISIiuiaNCl+nTp3CrFmzEB4ejqioKDz22GPIy8vzdm10A86W2CALEVJDjhfr3q4FAGBnTjEvuE1EREGlUeHL5XLBbrd7bldXV4dcb0qoCYXLCjUkLkqP1HgjSiprcKrA7O9yiIiIGq1R63zdeeedeOCBBzB27FhIkoQ1a9ZgxIgR3q6NbkB+Se0yE6Ha8wUAGR1jcbrIgt2Hi5ESZ4QyyBeSJSKi5qFR4WvmzJlISEjATz/9BFmWMXbsWIwfP97btdENqOv5SgrRni8AMBk06JQahYOnynEotxxd2vJ6o0REFPgaFb7uv/9+/P3vf8e4ceO8XQ81kfxiK6JMWoTpQntZkK5pMTiWX4nsE2VolxwBnaZRb2kiIiK/adQ4jdlshs3Gs8qChbXGiXKzPaR7vepo1Up0T2sBp0vG3mNc+JeIiAJfo7oJ9Ho9hgwZgo4dO8JgMHi2L1261GuF0fXLLw79+V4X65ASiZy8chw5XYEOrSL8XQ4REVGDrhq+jhw5gmHDhmHgwIFISEjwRU10gzzzvZrJ6u9KhYQ+N8Vhw658/HdfAUYNaAMVJ98TEVGAajB8rVmzBq+99hpSU1ORl5eHRYsWITMz01e1UQM2Z+Vfcd/2Q7VXHygotzV4v1CSFGtEu+QIHDtTibVbTmHMoLb+LomIiOiyGuweWLFiBdauXYvPP/8cS5cuxQcffOCruugGlJsdkCQgMkzj71J8qlenWITpVPjml1ycPFfl73KIiIgu66pjM/Hx8QCAHj16oLy83OsF0Y0RQqDCYke4QdPs1r3SqJQY0DUBshD48F8H4XS5/V0SERHRJRr8dP71KvZKpdKrxdCNs9W44HTJiDQ2r16vOokxYRiWkYxzpTZ8+eNJf5dDRER0iWvqGrnWSwrt3bsXU6dOvWT7xo0bMW7cOEyaNAmrVq26puekhpVbai8DFWnS+rkS/xl/axriovT4bnsesk9w+QkiIgosDU64P3z4MDIyMjy3a2pqkJGRASEEJEnC7t27r/jYDz74AF9//TX0en297U6nEwsWLMDq1auh1+tx7733YsiQIYiNjb3Bl0IAUGGuDV9RzTh8aTVKzLi7MxZ8tBtL/7kfz03rhdhYk7/LIiIiAnCV8LV+/frrfuKUlBQsXrwYTz75ZL3tx48fR0pKCiIiatdj6tmzJ3bu3Ik77rjjuo9FF1RYHACASGPzDV8A0CYxHL+7sxM+WHsQb6/eh7f+FO3vkoiIiABcJXwlJSVd9xOPGDECZ86cuWS7xWKByXShFyIsLAwWi+WqzxcVZYBKFZpzzq6nV8Zk1F12e6XVAZVSQmKcCYprHCYOFXXtefetJpRbnVi98SgW/mMnXni4X7M7CcEf2MvoG2xn32A7+0Zza2efXwjPaDTCarV6blut1nph7ErKy0Pz8kaxsSYUF5uv+XFmS80l22RZoLzKjiiTFlarvSnKC0oXt+ftvZNxLK8cWUeLsXjlHtz3mw5+rCz0Xe/7ma4N29k32M6+Eart3FCg9Hk3QFpaGnJzc1FRUQGHw4GdO3eiR48evi4jJFXZHJCFQKSpeZ7peDkKScLDo25GaoIJG3adwdotPAOSiIj8y2fha+3atVi5ciXUajWefvppPPjgg5g8eTLGjRvnWUuMbgwn21+eXqvC8w/2Q0y4Dl/+dBLf/HLK3yUREVEz5tVhx+TkZM9SEqNGjfJsHzp0KIYOHerNQzdL5Zxsf0Vx0QY8OaUHFn6yG2t+OAGFJOGOfqn+LouIiJohzj4OIez5alhspB5PTMlAdLgWn28+jv9sy/N3SURE1AwxfIWQCosdWrUSOk1onhXaFOIi9Xjy3h6IMmmxatMxrPnhOGQh/F0WERE1IwxfIcLpkmG2ORFl0l7zlQiam7goA56a0gPxUXp880suPlh7EE6X7O+yiIiomWD4ChGVdZcVaqbXdLxWcVEGPDO1J9olR2DbwUK88dkeWKqd/i6LiIiaAYavEMFrOl47k0GDJyano3enOBw5U4mXV+zCuVLr1R9IRER0Axi+QkSFufZMR062vzZqlRIzRnfGHf1SUFhmw7y/78Suw0X+LouIiEIYw1eIKDPXrnjPZSaunUKSMOHWdphxd2fIQuCvX+7H55uOwS1zHhgRETU9hq8QIIRAudkOk0ENtYo/0uvV9+Z4zJ3WC/FReny7LQ9vfJblmUtHRETUVHx+bUdqetV2FxxOGQnRBn+XEhA2Z+Vfss1k1F32epgXuzU9CUmxRsy9vzf+75uD2HO0BH9ZvgO/H3Uzbm4d7a1yiYiomWE3SQgo4+KqTcqgU2HW2K6YPLQdrNVOvPFZFr788QSHIYmIqEkwfIWAcoavJidJEob3ScH/+21PxETosPbnU3j90yxPWxMREV0vDjuGAIavpnG54UoAuK1XMn7eX4AjpyvwzPtbMbBbIpJiwzz7b01P8lWJREQUAtjzFQLKzXaolQoY9Wp/lxKSNGolBqe3RJ+b4uB0ydiw6wx2Hy6GLPOyREREdO3Y8xXk3G4ZVVYHWkToeFkhL5IkCZ1SoxAbqcePe89i/8kyFJZXY3B64hV7zK6GPWZERM0Te76CXIXVASGAKJPO36U0CzEROtw1IBWtE0worqjGv37ORWGZzd9lERFREGH4CnLlVZzv5WsalRKZ3RPRu1Mc7E431u04jUOnyiEEhyGJiOjqGL6CHCfb+4ckSbipdRSG924FrVqJHTlF+O++c3C5uRwFERE1jOEryDF8+Vd8tAEjB7RGbKQOJ8+ZsX7HadQ4XP4ui4iIAhjDVxCru6yQUc/LCvmTQafC8D6t0CbRhOKKGny7NQ9VVoe/yyIiogDFT+wgVm13w+50IzqcvV7+plQoMLBbIrqmxcBsc+LbrXkoKudEfCIiuhTDVxCrG3KMNDJ8BQJJktCjfQv07xIPh8uNdTvO4Eyxxd9lERFRgGH4CmLl5toLRXO+V2BpnxyJoRnJkABs3n0Wp4sYwIiI6AKGryBW1/PFYcfAkxQbhmE9k6FQAJv35COv0OzvkoiIKEAwfAWxcrMdKqXEywoFqIQYA4b1TIZSIeGHrLM4VcAARkREDF9Byy3LqLQ6EGnU8rJCASw+2oDberWCSqHAT3s5BElERAxfQavSUntZIQ45Br64KD1u613bA/Zj1lkUlVf7uyQiIvIjhq8g5TnTkZPtg0JspB6D01tCFgIbd59BxfmfHxERNT8MX0Gq7Pw1HaMZvoJGUqwRA7okwOGU8f2uMyirqvF3SURE5AcMX0GqtKoGEoDocJ2/S6FrkJYUgYyOsbDVuPDGyizYapz+LomIiHyM4SsIybJAWVUNIowaqJT8EQabzq2jcFNqFM6V2rD0nwfglnkxbiKi5oSf3EHoXKkVLrdATAR7vYKRJEno2SkW3dJisP9kGT7fdNzfJRERkQ8xfAWhuvWiGL6Cl0KSMOPuzkiMMWDdjtP4ae9Zf5dEREQ+wvAVhE6dqw1fLTjfK6jptSo8Nr4bwnQq/OO7wzhyusLfJRERkQ8wfAWhUwVVkCRe0zEUxEcZ8D/3dIEQwF+/zOYZkEREzQDDV5BxyzLyiiyINGqh5GT7kHBT62jce1t7mG1O/PXLbDhdbn+XREREXsRP7yBztsQGp0vmfK8QMzQjCQO6JODkOTM+Xn/U3+UQEZEXMXwFmVPnqgBwvleokSQJ00Z0REqcET/uPYsfOQGfiChkMXwFGZ7pGLo0aiVmju2KMJ0KH607jBNnq/xdEhEReQHDV5A5VVAFlVJCpEnj71LIC2Ij9ZgxujPcboElX2Wjyubwd0lERNTEGL6CiMst43SRBcmxRigV/NGFqi5tYjBmUFuUVdmxjCvgExGFHJW/C6DGyy+uXdm+dWK4v0uhJrA5K/+K+8L0KrSKM+JQbjne+nwvenaM8+y7NT3JF+UREZGXsPskiJwsqJ0D1DrB5OdKyNskScIt3RIQblDjwMlyz1w/IiIKfgxfQaRuZXuGr+ZBo1Li1owkqJQSfs4+hwqL3d8lERFRE2D4CiK5BWaoVQq0bBHm71LIRyKNWtzSNREut8Dm3flwOLkAKxFRsGP4ChJOlxtnii1IiTNCxZXtm5XUBBM6t4lGlc2JH7LOcgI+EVGQ89qEe1mW8cILL+Dw4cPQaDSYP38+UlNTPfvnz5+P3bt3IyysthdnyZIlMJk4nHYlZ4qtcMsCqRxybJZ6dGiBCosd+cVWrNxwDFN+08HfJRER0XXyWvj6/vvv4XA4sHLlSmRlZeHVV1/Fe++959l/4MABfPjhh4iOjvZWCSHl5PmV7Rm+mieFJCGzeyL+szUP3+86g5axYTzrkYgoSHlt/GrXrl3IzMwEAKSnp2P//v2efbIsIzc3F88//zwmT56M1atXe6uMkHH0TCUAoH1ypJ8rIX/RqJQYkpEEo16Nj9cdwaHccn+XRERE18Fr4ctiscBoNHpuK5VKuFwuAIDNZsNvf/tbvP766/jwww/xySefICcnx1ulBD0hBI6crkB4mAbxUXp/l0N+ZDJoMHNMFwDAki+zca7U6ueKiIjoWnlt2NFoNMJqvfDBIMsyVKraw+n1ekybNg16fW2Q6NevH3JyctCpU6crPl9UlAEqldJb5fpVbGzDQ4kFpVaUm+24pXtLxMXVLrBqMvLajtcqVNpsYM8U1LgF3l6Zhf/9fB9e/0MmWkQGTii/2vuZmgbb2TfYzr7R3NrZa+ErIyMDmzZtwp133omsrCx06HBhgvCpU6cwe/ZsfPnll5BlGbt378aYMWMafL7ycpu3SvWr2FgTiosbXkDzl33nAACt44ye+5otNV6vLZSYjLqQabPiYjO6t4nGuMFtseaHE3j2vS14+r4MGPVqf5fWqPcz3Ti2s2+wnX0jVNu5oUDptfD1m9/8Blu2bMHkyZMhhMArr7yC5cuXIyUlBcOGDcOoUaMwceJEqNVqjB49Gu3bt/dWKUHvyOkKAECHVpzvRRfc2S8VVVYn1u88jbdX78WcST2g1YRm7zARUSjxWvhSKBR46aWX6m1LS0vzfP/www/j4Ycf9tbhQ8qR0xUwaFVIiuXiqnSBJEmYNKwdzNUObD1QiCVf7cessV2hVnEdOCKiQMbf0gGu3GxHUUU1OrSKhEKS/F0OBRiFJGH6nTehS9toZJ8oxV+/zIbTxVXwiYgCGcNXgKsbcmzfKsLPlVCgUikVmDWmKzq3ica+46VYvCablyEiIgpgDF8BjvO9qDE0aiUeG9cV3dJisP9kGd5Zsw92BjAiooDE8BXgjpyugEatQGp88zoNl66dWqXEzDFd0aN9Cxw8VY63Vu1Ftd3l77KIiOhXvDbhnm6c2eZAfokVN7eO4sW0yWNzVn6D+29uE43SqhocPl2B5z7chmE9k2HQqXg5IiKiAMFP9ABWd0khDjnStVAqJAxKb4kOrSJRbrbj31tzUWG2+7ssIiI6j+ErgNXN9+rI8EXXSCFJ6HtzHHp0aAFbjQv/2ZaHw3m8FiQRUSBg+Apgh09XQKWU0CYx3N+lUBCSJAld28bglq4JcLplvLEyCz/uPevvsoiImj2GrwBVbXchr9CMNonh0Ki5ajldv7SkCNzWKxlatRJ/+zYHH607DJdb9ndZRETNFsNXgDqWXwkhON+LmkZiTBjm3t8LSbFh2Lg7H298loUqm8PfZRERNUsMXwHqwMkyAECnlCg/V0KhIi7KgGen9kTPDrE4fLoC8/62A7kFoXcxWyKiQMfwFYCEENhztBg6jZI9X9SkdBoVHh3TBWMy26C0yo4FH+3C1oMF/i6LiKhZYfgKQPklVhRX1KBr2xheJJmanEKSMOqWNnhsXDcoFBLe//ogVm06BlkW/i6NiKhZ4CKrAWjP0RIAQI/2LfxcCYWSyy3OOrxPK2zanY//bMvDvuMlyOzWElpN/RM8uDgrEVHTYrdKAMo6WgylQkK3tBh/l0IhLtKoxV39U5EUG4azJTZ880suSqtq/F0WEVFIY/gKMOVmO06eM6NDq0gYdGp/l0PNgEatxJCMJHRLi4Gl2on/bM3D8fxKf5dFRBSyGL4CTNYxDjmS7ykkCentW2BoRhKUCglbsguw9UAB3DLXAyMiamoMXwFmz9FiAEA6wxf5QXKcEXcNSEWUSYsjpyvx3bbTKOMwJBFRk2L4CiDVdhdycsuREmdEiwi9v8uhZspk0OCOfilo2zIcJZU1ePFvO3Aol9eFJCJqKgxfAWT/yTK43IK9XuR3KqUCt3RNQJ+b4mCrcWHRZ3vw7bZcCMHlKIiIbhTDVwCpG3Ls0T7Wz5UQ1V6Yu1NqFJ6akoGIMA0+33Qci9dkw1Lt9HdpRERBjeErQLjcMvYdK0V0uBYp8UZ/l0Pk0S45An/5XR/clBqFrGMleHH5Dhw/y7MhiYiuF8NXgDh6ugI2uwvp7VpAkiR/l0NUT0SYBn+elI7RA9ugrKoGr360G+u250HmMCQR0TVj+AoQ/82uvb5ez45xfq6E6PIUCgmjB7bBnyenI0ynwmcbj+HNlVk8G5KI6BoxfAWAKpsDO3IKkRBtQKcUXkibAtvNraPx4vQ+6JYWg4OnyvH8/23H1gMFnIxPRNRIDF8B4Ke9Z+FyCwzNSOKQIwWFCKMWfxzfDfff3hFuWeD9tQfx3j8PoLSy2t+lEREFPF5Y28/cbhmb9uRDq1ZiQJdEf5dDdInLXZD7Ynf2T8F/9xVgZ04RHnr5e3RLi8ZNraMxLCPZRxUSEQUX9nz52faDhSirsmNAlwQYdMzCFHxMBg1u79sK/TvHQ6WUsPtICdb+9yT2HivhUCQR0WXw097PvtlyAgAwNCPJz5UQXT9JktC+VSRuTmuBLVn5OJxXgbdX70NKnBG390tB705xUCr4tx4REcDw5VdnS6zYe7QEnVIikRTLtb0o+Ok0KvS5OR7tW0WioNSGnYeL8P7XB/HFDycwrGcyeneKQ3S4rsHnuNow55Xcms4/YIgoODB8+dGm3bUfMkM5N4ZCTJRJizGZbVFUbsN3O07jv/vOYeXGY1i58RjatgxHzw6x6NauBRJjDFDwJBMiamYYvvyk2u7Clv3nEBOhQ48OvJYjhaa4KAOmDu+I0QPbYGdOEXYdLsbhvAqcOFuFzzcfh1ajREqcEakJJiTHGhFp1KLcXAO9VgWtWsmzf4koJDF8+cnmPfmocbgxfmh7zoWhkBdu0GBoRjKGZiTDbHMg62gJcvIqkFdoxrH8Shw9c+nliiQJ0KiU0KgV0KgUUKuV0KgU0FzyrwIalRLHz1aiRYQe4QY1QxsRBTSGLz8oq6rB11tOwahX485b2qDGavd3SUQ+YzJokNm9JTK7twQA2J1unC6yoLDMhgqLHftPlqHa7kK13QWnS4bDKaPS7oDL3fCZkxvPD+Nr1ArERugRF6VHcqwRreKMSI4zIi5SD4WCoYyI/I/hyw8+3XAUdqcbU37THiaDhuGLmjWtWol2SRFolxQBAAjTqy97P1kWcLjccDhlOFwyHE43nC4ZdqcbDpeMFuE6lFTWoKSiGsWVNcgvsWLP0ZILx9EokdYyHO2SItA+ORJtW4ZDr+WvQCLyPf7m8bF9x0ux63Ax2iVH4JauXFSVqLEUCgk6jQo6zZXvkxBj8HxfbXeh3Gz3fJVW1uDgqXIcPFUOAJAARJq0SG/fAu3PB7KYiIbPxCQiagoMXz7kcLrx8frDUEgSpg3vyLO8iLxIr1VBr1WhZYswz7YahxslFdUoKq9GUUU1SitrsGl3vufMY4NOhbio2iHL+Cg9Io3aK84f49IWRHS9GL586JtfclFcUYMRfVohOY7rehH5mk6jRPL5OWAA4JYFyqpqUHw+jBWVV+PUOTNOnTMDANQqRW0Yi9QjNlKP6HAtNGqlP18CEYUAhi8fOVtixbfbchFl0mL0wDb+LofI6653sVRfUiokxJ4PVjcDEELAbHOisLwaReU2FJVXI7/Yivxiq+cxJoMa0eE6VNe4kJJgQmq8CcYrzFMjIrochi8fKKmsxpursuByC0y5rT10GjY7USCSJAnhYRqEh2nQPrn2BIBquwtF5dUoqaxGaZUdZVU1yC0wI7fA7HlcTLgOKfFGJMfW9qolx4YhLkrPZWSI6LKYAryswmLHos+yUFZlx7jBbdGzY5y/SyKia6DXqpCaYEJqgglAbe+YtdqF0qoalFXVoKzKjtKqGuw5WlLv7EqFQkKkUYNIoxZRJq3n3zv6pnAdMqJmjuHLiyzVTrzxWRaKyqsxckAq7urf2t8lEdENkiQJRoMaRoO6XiCrcbg9Z1ZWmO0ot9hRaXGgrKr+UjLfbs2t7SGLNSIpLqz23xZhXPaCqBnh/3YvsVQ78cbKLOSXWHFbr2SMyWzr75KIyEskSbrs2ZWyEDBbnaiwnA9lFjtqHG4cOV2Bw6cr6j1HiwgdUuNNSIk3IiXehJR4EyKNGvaSEYUghq8mJoTA1gOF+HTDUViqncjsloh7h7XnL1CiZkghSYgwahBh1Hh6yQDA6ZJRabWj3Ozw9JKVV9mx60gxdh0p9txPp1EiOlyLaJMOA7slIjXehNgovT9eChE1IYavJlRUbsOK7w7jwKlyaNQKTBzSDsN7t2LwIqJ61CoFWkTo0SLiQpASQsBW40KZ2e6ZS1ZWVYOzJTacLbFh/8kyALWBrG1SBOIj9UiINiAhxoCEaANiwnW8fBJRkGD4ukFuWcah3HJsO1CI7TlFcLpkdGkbjanDOyI2kn+hElHjSJKEML0aYXo1Wl20DqDd4UaZuQZRRh3yiszIK7Qg51QZDv7qUpcKSUKkSYMoU21PWXiYBmE6FQxaFQw6NbQaJVQKCUql5DkL0+mW4XLJcLnl2u/dAs7zt4+croDLLZ//urC97l+3LCBEbWgUAhCo/Vc+f1uSAJVScf6r9pgqpeS5rVYpoFZduDh693YtYNCqYdCqoPfUrYJGpeAfsNfpepd74QLC3ue18CXLMl544QUcPnwYGo0G8+fPR2pqqmf/qlWr8Nlnn0GlUuHRRx/FkCFDvFVKk5JlgaKKauQVmnHsTCW25xShyuoAUDtnY9zgNPS5KY6/LIioSWg1SiTGhNX7QDRF6LH/cBEKy20oKLWhoMyGksoalJtrcPKsGcdFldfqUUiASqWAUiFBkiRIqD2zU5IkKCQJklQbJIUQcLkFHE43bDXyVS+Mvu1g0WW3KxW18+kMFwUyvfbC94bzc+1qv1d7tmk1SmjUF8JdIC77IYSALARcLgGXXNtGLpdc+73r/O2672Xh2eaWa0OwW64NxW73RftlGS6XgNMtI6/QDFkWcJ//uvh7IS78PES9bwR+yDoLpaI2KKvrArNKAfX5MF0bnBXQqpXQqOv+VUJ7/qtu2+X2s3e2ltfC1/fffw+Hw4GVK1ciKysLr776Kt577z0AQHFxMVasWIE1a9bAbrdjypQpuOWWW6DRNHDRNi8TQiC30IwqqxMOpxsOlxs1DjeqrA6YbU5UWR0oM9uRX2KBwyl7HmfUqzGkRxL6dY5HWlIELxlERF6n09Rf/uJisixQaXXAbHPAVuPC9pxC2J21vVVCrv2wl89/2ioUEpQXfSku+lelUEClqvsArv3wVSlrQ9f1qBc0zve0OZ2y52LprRPDYatxwmZ3obrGBZvddcn3FWY7HC756ge7DIUEKJUXet+UCglRJh20agU0auWlbSBJMBg0cDpcnsAgn+/pk+WLe/lq29PtvnpYstW4akOQuBCE/EECLnQQSLW3PfskoNLqgCzXvr6mplIqPG1eG8gUMBo0kICrBjeNWgGtSgnN+V5c6aKwL0m4EP7xq9uSdD5XCgjUbk+IMfj189pr4WvXrl3IzMwEAKSnp2P//v2effv27UOPHj2g0Wig0WiQkpKCnJwcdOvWzVvlXNX+k2X431V7G7yPUiEhMSYMreKMnjOS2idHQKUMvL+oiKh5UigkRJlq1xQDgIJym58rqiVJEpSSBKUG0OLSSzQ1dqjL5Zbrh7IaF3YeLjr/R7Nc++V0e4ZLPaHo/FCpyy3D7RawO92w1ljgvM4wdzUKSao3zKpUKqA8P9x6cchVKGrbRfGr8KuQLnzfJjHc0wOlPN8bpTwfipWeY1wULJUS1EoF9hwtPv+cikvCdWPUBeaLe808vWfn29R1Ufu2bRkBu8MNh9MNu8sNh0OG/Xxnht1R+/OxO92125xuVNtdqLC4cbrIAi/kvAaNGtAaYwb5bxUCr4Uvi8UCo/HCvAWlUgmXywWVSgWLxQKT6cJfbGFhYbBYLA0+X2zspX/hNaWhsSYM7dvaq8e4kut5bRN+08kLlRBRsGjs743m8Lvi1j6pV79TM9SzSyRFLzYAAA+0SURBVEt/l0BX4LUuG6PRCKv1wvXQZFmGSqW67D6r1VovjBERERGFKq+Fr4yMDPz4448AgKysLHTo0MGzr1u3bti1axfsdjvMZjOOHz9ebz8RERFRqJKE8M5Ia93ZjkeOHIEQAq+88gp+/PFHpKSkYNiwYVi1ahVWrlwJIQRmzJiBESNGeKMMIiIiooDitfBFRERERJfiaXpEREREPsTwRURERORDDF8+Issynn/+eUyaNAlTp05Fbm5uvf2rVq3C2LFjMXHiRGzatMlPVQa/q7Xz/PnzMXbsWEydOhVTp06F2Wz2U6WhYe/evZg6deol2zdu3Ihx48Zh0qRJWLVqlR8qCx1XauPly5fjrrvu8ryXT5w44YfqQoPT6cQTTzyBKVOmYPz48diwYUO9/Xw/N42rtXOzek8L8onvvvtOPPXUU0IIIfbs2SMeeeQRz76ioiIxcuRIYbfbRVVVled7unYNtbMQQkyePFmUlpb6o7SQ8/7774uRI0eKCRMm1NvucDjEbbfdJioqKoTdbhdjx44VRUVFfqoyuF2pjYUQ4s9//rPIzs72Q1WhZ/Xq1WL+/PlC/P/27j4oqvKLA/h3eSdAx3UKG4smQCEh0KjBhWxDI52WdfGNEAQ0CW2AUgxBIyA0R4lplAxF8+WfGlJBU2jyBbVGBJKhiCxBTGAh3PAVcVGW3fP7g+HGCqzSDxaF85lhhvvcvfee8/AMc+a5d59LRNevXyepVCrs4/E8cAz1M9HIGtM882UkD7viv52dnbDiP+s/Q/2s0+lQV1eH5ORkBAcH48CBA0MV5rDg4OCAL774okf7pUuX4ODggNGjR8PCwgJeXl4oKysbgggff331MQCcP38eO3bswMKFC5GdnW3kyIaXWbNm4YMPPhC2TU3/XYGfx/PAMdTPwMga04O2wj3TN9Ar/rPeGepntVqNRYsWYcmSJdBqtQgPD4e7uztcXYf/CuCDYebMmWhoaOjRzuN54PTVxwAgk8kQEhICW1tbxMTE4NSpU/Dz8zNyhMODjY0NgM6x+/7772PFihXCPh7PA8dQPwMja0zzzJeR8Ir/xmGon62trREeHg5ra2vY2tpi6tSpPMM4CHg8Dz4iQkREBMRiMSwsLCCVSvHHH38MdViPtaamJoSHh0OhUEAulwvtPJ4HVl/9PNLGNBdfRsIr/huHoX6ura1FSEgItFotNBoNysvL4ebmNlShDltOTk6oq6vDzZs30d7ejrKyMkyZMmWowxpWWltbERAQgDt37oCIUFpaCnd396EO67F19epVvPPOO4iPj8f8+fP19vF4HjiG+nmkjWm+7Wgk/v7+KCoqQnBwsLDi/549e4QV/8PCwhASEgIiwsqVK2FpaTnUIT+WHtTPcrkcQUFBMDc3h0KhwIQJE4Y65GHjyJEjUKvVePvtt5GYmIilS5eCiDBv3jzY29sPdXjDQvc+XrlyJcLDw2FhYQGJRAKpVDrU4T22tm/fjpaWFmRlZSErKwsAsGDBArS1tfF4HkAP6ueRNKZ5hXvGGGOMMSPi246MMcYYY0bExRdjjDHGmBFx8cUYY4wxZkRcfDHGGGOMGREXX4wxxhhjRsTFF2OPiLCwMOzYsaNH++7du/Hee+8ZPDYxMRG7du0arNAEra2tCA4Ohkwmw7Fjx3rEMG3aNCgUCigUCrz11ltITk5Gc3MzAEClUiE4OPiB15g+fToqKyv7FZdSqURsbGy/jumutLQUHh4eUCgUCAwMhEKhwNy5c3Hy5Ml+nysgIAClpaUPne9AaGhowAsvvCD0fdfPli1bBvxap0+fFs5bWFiI9evXD/g1GBvueJ0vxh4RISEh2Lx5M6KiovTa9+3bh6SkpCGKSt+ff/6Ja9eu4fjx473uX7x4MZYuXQqgc8Xq7OxsREZGIi8vD/b29sjJyRmUuP7++29cvnz5/zqHg4MDvvvuO2H7woULWLhwIQoLCyEWi/t9vsHMtzdWVlZ68Q+WyspK3Lp1CwAwY8YMzJgxY9Cvydhww8UXY48If39/bNiwAWVlZXj55ZcBAD///DOICL6+vtDpdNiwYQMqKiqEVaDXr18PLy8vvfO4uLiguLhYKBi6b588eRLbtm2DRqOBlZUVEhISel2t+8SJE9i6dSt0Oh1sbGywZs0a2NraYu3atVCpVFAoFPj2229hZWXVZz4ikQjLly/HwYMHUVRUBEdHR8jlcvzyyy+4evUqkpOTce3aNTQ3N2P8+PHYvHkzxo4dCwD45ptvcOHCBbS3t2PJkiXCati9xe/h4YGkpCSoVCosXboUu3btQnl5OTIyMtDW1gYTExPExMTAz88Pzc3NSEhIwI0bNwAAUqm0x/vluri6usLKygqNjY0Qi8XYtm0bjh07Bp1Oh/HjxyMlJQX29vaoqanB2rVr0dbWBkdHR6jVagCds1Fd+ba1tSElJQUVFRWws7ODs7MzAGDjxo2YPn06PDw8UFVVhbi4OHh4eCAtLQ1NTU3QaDSQyWRYvnw5APSZlyHd47h/Oy8vD8ePH4eJiQnq6upgZWWFTZs2wcnJCc3NzUhJScFff/0FExMTBAcHw9PTEzk5OdBqtbCzs8Nzzz2Ho0ePIjs7G1euXEFqaioaGxtBRAgMDERkZCQaGhqwePFiSKVSVFRUoKWlBfHx8fD39zcYN2PDGjHGHhmZmZmUkJAgbMfFxdHevXuJiKi8vJxiY2NJq9USEVF2djYtW7aMiIgSEhLoq6++IiKiiRMn0rVr14RzdG1fvnyZAgIC6Pr160REVF1dTb6+vnTnzh29GGpqasjHx4fq6+uJiOjs2bPk6+tLt2/fppKSEpLJZL3G3j2G7mJjY2nnzp2kVCpp8uTJRES0d+9eys7OJiIinU5HkZGRtGvXLiIi8vPzo5SUFCIiunLlCkkkEqqurjYYf/e4bt68SW+++SYplUrhHK+99ho1NjbS1q1b6eOPPyYiojt37tCKFSuopaWl17yOHj1KPj4+pFar6eDBg7RixQrSaDRERJSTk0ORkZFERKRQKGjfvn1ERFRWVkYuLi5UUlKil29GRgbFxcWRVqul27dvk1wuF/7Ofn5+tHXrVuG6YWFhVFhYSEREd+/epbCwMCooKDCYl1KpJFdXV5o9e7bwM2fOHCIivTju387NzSUvLy9qamoiIqK0tDRavXo1ERFFR0fTpk2biIiopaWFZDIZ1dbWUmZmJn3yySfC8VFRUUREFBoaSrt37xY+L5fLKT8/n5RKJU2cOJFOnjxJREQ//PADvf766z3GCWMjCc98MfYICQoKgkwmQ2trKzo6OnDmzBmkpqYCAKZMmYLRo0cjJycHSqUSpaWlsLGxeehzFxUV4Z9//sHixYuFNpFIhPr6eri6ugptJSUlmDp1Kp599lkAgEQigVgsxu+//w6RSNTvnEQiEaytrfXaIiIiUFZWhj179qC2thYXL16Ep6ensL/rWSl7e3v4+vqiuLgYpqamfcbf3a+//orm5mZER0frfa6qqgrTpk1DVFQUmpqa4OPjg1WrVgkvSa6vr4dCoQAAdHR0YNy4ccjKyoK1tTVOnTqFyspKzJs3D0DnC9vb2tpw48YNVFVVITAwEADg5eXV6yurfvzxR6xZswYmJiawtbXFnDlzUFVVJezvmulUq9U4d+4cbt26JTxXpVarceHCBdjY2PSZ14QJE/7zbUc3NzeMGzcOADBp0iThlvLZs2cRHx8PALCzs0N+fn6f51Cr1SgvL8fu3buFz8+dOxc//fQTPD09YW5uLrwqZtKkSbh582a/42RsOOHii7FHiL29PXx8fPD9999DrVZj5syZQnFw+vRpfPrpp1iyZAlmzJgBR0dHHD582OD52tvbhd91Oh0kEgk2b94stDU1NeGpp57SO0an0/UosogIHR0dMDc371c+RITz589j0aJFeu2fffYZfvvtN8ybNw/e3t7o6OgAdXvTmYnJv98F0ul0MDMzg1ar7TP+srIyoU2r1cLJyQn79+8X2lQqFcRiMczNzVFYWIji4mKUlJRgwYIF2LlzJ4Cez3zd3yeRkZEICQkB0NmvXc89deXZxcys579VMzOzPvMDgCeeeEK4DhEhJydHKFivX78OS0tLlJaW9pmXSqXqNW6gs0Drfm2NRqO3v/ut4+6fNTMz0xsHSqUSY8aM6fUaXXHf39bR0QEAMDc3F3L+LwU8Y8MNf9uRsUdMaGgojhw5gkOHDiE0NFRoLyoqgp+fH0JCQuDu7o4TJ05Aq9X2OF4sFgvfFuw+WyGRSFBUVIRLly4B6JyNmT17Nu7evat3vEQiwZkzZ6BUKgEAxcXFaGpq0puZehharRZffvklxowZg1deeUVv35kzZxAREYHAwECMHTsWZ8+e1cvl4MGDADofpC8uLoZEIjEYv6mpqVBUTJ48GXV1dTh37hyAzi8JzJw5EyqVChkZGcjKysIbb7yBjz76CM7Ozrh48eIDc3n11Vdx4MABtLa2AgC2bNmC1atXY8yYMXBzcxMKovPnz6O6urrH8VKpFLm5ucKMWX5+fq9FiK2tLSZPnow9e/YAAFpaWoSH/g3lZcioUaOg0WhQU1MDACgoKHhgvkDnOMjNzQUA3L59GxEREaitrYWpqalQVHWP29PTE19//bXw+UOHDsHHx+ehrsXYSMMzX4w9Yry9vbF+/XqMHj0aLi4uQntwcDBWrVoFuVyOjo4O+Pr6Cg+Ad5eUlIS0tDSMGjUKPj4+ePLJJwEAzs7OSEtLQ1xcHIgIZmZm2LZtW49bl87OzkhJSUFMTAy0Wi2srKywfft2YQbOkL179+Lw4cMQiUTQarV48cUXe10+Izo6Gunp6diyZQvMzc3x0ksv6d0+vHfvHubMmQONRoOkpCQ8//zzANBn/M7OzrC0tMT8+fOxf/9+ZGZmIj09Hffu3QMRIT09Hc888wwiIiKQmJiIgIAAWFhYwMXFBTKZTHgYvS8LFiyASqVCUFAQRCIRnn76aWzcuBEA8Pnnn2PNmjXIycmBg4MDHB0dexy/bNkypKWlQS6Xw87ODmPHju3zywoZGRlYt24d5HI52tvbERAQgNmzZwNAn3k1NDT0GbudnR3i4+Px7rvvQiwWY9asWQZz7ZKcnIzU1FTI5XIQEZYtWwZ3d3e0t7fjww8/xLp16+Dm5qYXd1paGvLy8tDe3g65XI65c+eisbHxoa7H2EgiovvnihljjA2ogoIC2NraQiqVQqfTITY2Fr6+vsJtTMbYyMLFF2OMDbLq6mokJyejra0NGo0G3t7eWLt2bb+foWOMDQ9cfDHGGGOMGRE/cM8YY4wxZkRcfDHGGGOMGREXX4wxxhhjRsTFF2OMMcaYEXHxxRhjjDFmRFx8McYYY4wZ0f8Arhr85GzO+9oAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xf2b7a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAmQAAAFKCAYAAACzX0NnAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzs3Xl8VNXdP/DPrEkmM0kmOyRkhRAWYwiLC4RFRZSiIgrSWNTSWvQBtVgV6iMWERF41EetdXtqUeMCqVDb6o8qq8gOgQABwpJAgOx7ZklmPb8/AgMRCAEzubN83q8XLzL33rnzPVwgn5x77jkyIYQAEREREUlGLnUBRERERP6OgYyIiIhIYgxkRERERBJjICMiIiKSGAMZERERkcQYyIiIiIgkxkBGRG7Vt29f1NfXt9u2atUqzJgxAwDw1ltv4euvv+7wHO+88w7Wrl3rthrd6fDhw7jtttswadIknDlz5pLHPPHEE7jhhhvQ0tLSzdURkadgICMiST311FOYOHFih8fs2LEDdru9myrqWuvWrcMNN9yAVatWIT4+/qL9VVVV2LVrFzIzM68YTInIdymlLoCI/NvcuXPRp08f/OY3v8Hbb7+NNWvWQKVSQa/X49VXX8WaNWtQWFiIpUuXQqFQ4MYbb8RLL72EoqIiyGQyZGdn4+mnn4ZSqcQPP/yA1157DXK5HP369cPWrVvxxRdfYOfOnfjqq6/Q0tICrVaLDz74APPnz0dpaSkaGxsRHByM1157DSkpKZg2bRoGDBiAgoIC1NfXY8qUKaitrcXOnTvR0tKCN998E3379r2oHX/5y1/w7bffQqFQIDk5GfPmzcO2bdvw5ZdfwuFwoLW1Fa+//vpF78vLy8NNN92EcePG4a233sLUqVMhk8kA4LLtiY+Px9///nd8+eWXcDqdCAsLw7x585Camur260VEbiKIiNwoLS1NTJgwQdx9992uX6NGjRK/+93vhBBCzJkzR/z1r38V5eXlIisrS1gsFiGEEB999JFYs2aNEEKIX/3qV2L16tVCCCGee+458fLLLwun0yksFouYPn26+OCDD0R9fb0YNmyYOHz4sBBCiFWrVom0tDRx+vRpsXLlSjF06FBhMBiEEEKsXr1avPzyy64a582bJxYsWOD6rFmzZgkhhCgoKBBpaWli3bp1QgghXnnlFfHCCy9c1MavvvpKPPDAA8JkMgkhhHj77bfF9OnTXV+/9NJLl/yzsdlsYsSIEWL9+vXCYrGIoUOHio0bNwohRIft2bFjh8jJyRFms1kIIcSPP/4o7rjjjqu8MkTkSdhDRkRu98knnyA8PNz1etWqVfjuu+/aHRMTE4P09HTce++9GDlyJEaOHImbbrrponNt2rQJX375JWQyGdRqNaZOnYpPPvkEycnJSE1NRXp6OgDg3nvvxcKFC13v69u3L7RaLQDgjjvuQK9evZCbm4vS0lLs3LkTgwYNch07duxYAECvXr0AANnZ2QCAhIQE7Ny585I1TZo0CRqNBgDw0EMP4f3334fVau3wz2XdunVwOp3Izs6GUqnE+PHj8emnn2LUqFHYvXv3ZduzceNGlJaWYurUqa5zNTc3o7GxEWFhYR1+JhF5JgYyIvIIcrkcn332GQ4cOIBt27Zh0aJFyM7OxnPPPdfuOKfT6bqld+613W6HQqGA+MnSvHL5+WGy58ISAHzxxRfIy8vDgw8+iLvuugthYWHtBtyr1ep251GpVB3WfrmaruSLL75Aa2srbr/9dgCA1WpFTU0Njh071mF7nE4n7rnnHjz77LOu19XV1QgNDb3iZxKRZ+KgfiLyCEVFRZgwYQJSU1MxY8YMPPLIIzhw4AAAQKFQuALOiBEj8Nlnn0EIAavViry8PNx8883IysrCyZMnUVRUBAD47rvv0Nzc3C4onbN582bce++9mDx5MpKTk7F+/Xo4HI5rrj07OxsrV66E2WwGAOTm5mLo0KEXBbsLnThxArt27cKqVauwfv16rF+/Hps3b8bQoUPx6aefdtieESNG4Ntvv0V1dTUA4Msvv8TDDz98zfUTkfTYQ0ZEHiE9PR133nkn7rvvPmg0GgQGBuKFF14AANxyyy144403YLPZ8MILL2DhwoW46667YLPZkJ2djcceewxqtRpvvPEG5syZA7lcjoEDB0KpVCIoKOiiz5o+fTpefPFFfPXVVwCAzMxMHD169Jprv//++1FRUYHJkyfD6XQiMTERr732Wofv+fLLL3HbbbchMTGx3faZM2dixowZmD179mXbM2LECDz66KOYPn06ZDIZtFot3nnnnUuGTyLyDjLx0z5xIiIvZDQa8e677+KJJ55AUFAQDh48iBkzZuDHH3/0yqDia+0hoo6xh4yIfIJWq4VKpcL9998PpVIJpVKJN99802vDi6+1h4g6xh4yIiIiIolxUD8RERGRxBjIiIiIiCTGQEZEREQkMa8f1F9TY+iS8+j1GjQ0mLvkXN7In9vvz20H/Lv9/tx2wL/b789tB9h+KdsfFaW75Hb2kJ2lVCqkLkFS/tx+f2474N/t9+e2A/7dfn9uO8D2e2L7GciIiIiIJMZARkRERCQxBjIiIiIiiTGQEREREUmMgYyIiIhIYgxkRERERBJjICMiIiKSGAMZERERkcQYyIiIiIgkxkBGREREJDEGMiIiIiKJef3i4uReGwvKrvo9ozPj3FAJERGR72IPGREREZHEGMiIiIiIJMZARkRERCQxBjIiIiIiiTGQEREREUmMgYyIiIhIYgxkRERERBJjICMiIiKSGAMZERERkcQYyIiIiIgkxkBGREREJDEGMiIiIiKJMZARERERSYyBjIiIiEhiDGREREREEmMgIyIiIpIYAxkRERGRxBjIiIiIiCTGQEZEREQkMaW7Tux0OjF//nwcOXIEarUaCxcuRGJiomt/Xl4eli9fDqVSiccffxxjxoxBeXk5nnvuOQghEBoaitdffx1BQUHuKpGIiIjII7ith2zt2rWwWq1YsWIF/vCHP2Dx4sWufTU1NcjNzcXy5cvx0Ucf4Y033oDVasXHH3+MO++8E59//jn69OmDr776yl3lEREREXkMtwWy/Px8ZGdnAwAyMzNRWFjo2rd//34MGjQIarUaOp0OCQkJKCoqQr9+/dDc3AwAMBqNUCrd1oFHRERE5DHclniMRiO0Wq3rtUKhgN1uh1KphNFohE6nc+0LDg6G0WhEbGwsXn/9dXzzzTewWq2YNWvWFT9Hr9dAqVR0Sc1RUborH+TDLtV+nTawS87j6byx5q7kz+3357YD/t1+f247wPZ7WvvdFsi0Wi1MJpPrtdPpdPV4/XSfyWSCTqfDiy++iFdffRXZ2dnYuHEj5syZgw8//LDDz2loMHdJvVFROtTUGLrkXN7ocu03GFuv+lze9ufIa++/7ffntgP+3X5/bjvA9kvZ/ssFQbfdsszKysKmTZsAAAUFBUhLS3Pty8jIQH5+PiwWCwwGA4qLi5GWloaQkBBXz1l0dLTr9iURERGRL3NbD9nYsWOxZcsWTJ06FUIILFq0CMuWLUNCQgJuvfVWTJs2DTk5ORBCYPbs2QgICMC8efOwYMECOJ1OCCHw4osvuqs8IiIiIo8hE0IIqYv4Obqqy5Hdt5du/8aCsqs+1+jMuK4oqdvw2vtv+/257YB/t9+f2w6w/X51y5KIiIiIOoeBjIiIiEhiDGREREREEmMgIyIiIpIYAxkRERGRxBjIiIiIiCTGQEZEREQkMQYyIiIiIokxkBERERFJjIGMiIiISGIMZEREREQSYyAjIiIikhgDGREREZHEGMiIiIiIJMZARkRERCQxBjIiIiIiiTGQEREREUmMgYyIiIhIYgxkRERERBJjICMiIiKSGAMZERERkcQYyIiIiIgkxkBGREREJDEGMiIiIiKJMZARERERSYyBjIiIiEhiDGREREREEmMgIyIiIpIYAxkRERGRxBjIiIiIiCTGQEZEREQkMQYyIiIiIokxkBERERFJjIGMiIiISGIMZEREREQSYyAjIiIikhgDGREREZHEGMiIiIiIJMZARkRERCQxBjIiIiIiiTGQEREREUmMgYyIiIhIYgxkRERERBJjICMiIiKSGAMZERERkcQYyIiIiIgkxkBGREREJDEGMiIiIiKJMZARERERSYyBjIiIiEhiDGREREREEnNbIHM6nXjxxRfxwAMPYNq0aSgtLW23Py8vD5MmTcKUKVOwYcMGAIDZbMZzzz2HnJwcTJ48Gfv373dXeUREREQeQ+muE69duxZWqxUrVqxAQUEBFi9ejPfeew8AUFNTg9zcXKxcuRIWiwU5OTkYPnw4PvroI/Tp0wdLly5FUVERioqKkJGR4a4SiYiIiDyC23rI8vPzkZ2dDQDIzMxEYWGha9/+/fsxaNAgqNVq6HQ6JCQkoKioCJs3b4ZKpcJvfvMbvPvuu673ExEREfkyt/WQGY1GaLVa12uFQgG73Q6lUgmj0QidTufaFxwcDKPRiIaGBjQ3N+Ojjz7C119/jSVLlmDp0qUdfo5er4FSqeiSmqOidFc+yIddqv06bWCXnMfTeWPNXcmf2+/PbQf8u/3+3HaA7fe09rstkGm1WphMJtdrp9MJpVJ5yX0mkwk6nQ5hYWG45ZZbAABjxozBhx9+eMXPaWgwd0m9UVE61NQYuuRc3uhy7TcYW6/6XN7258hr77/t9+e2A/7dfn9uO8D2S9n+ywVBt92yzMrKwqZNmwAABQUFSEtLc+3LyMhAfn4+LBYLDAYDiouLkZaWhsGDB+OHH34AAOzatQu9e/d2V3lEREREHsNtPWRjx47Fli1bMHXqVAghsGjRIixbtgwJCQm49dZbMW3aNOTk5EAIgdmzZyMgIAAzZszACy+8gAceeABKpRJLlixxV3lEREREHsNtgUwul2PBggXttqWmprq+njJlCqZMmdJuf1hYGN555x13lURERETkkTgxLBEREZHEGMiIiIiIJMZARkRERCQxBjIiIiIiiTGQEREREUmMgYyIiIhIYgxkRERERBJjICMiIiKSGAMZERERkcQYyIiIiIgk1qlAtn79eggh3F0LERERkV/q1FqWubm5WLhwIe6//35MnjwZUVFR7q6LvNjGgrKrOn50ZpybKiEiIvIOneohW7ZsGT7++GOYzWZMmTIFTz31FLZt2+bu2oiIiIj8QqfHkCUkJGD27NmYO3cuCgsL8fTTT+Ouu+7C/v373VkfERERkc/r1C3L0tJS5OXl4Z///Cf69u2L559/HmPGjMG+ffvw+9//HuvXr3d3nUREREQ+q1OBbPLkybj33nvx2WefISkpybV90KBBGDZsmLtqIyIiIvILnQpk8+bNw1133dVu29dff42JEydi8eLFbimM/MfVPgQA8EEAIiLyLR0GsvXr18Nut+Ott95CYGCga+oLu92OP//5z5g4cWK3FElERETkyzoMZIcPH8b27dtRV1eHTz/99PyblEo88sgj7q6NiIiIyC90GMhmzpyJmTNn4vPPP8eDDz7YXTURERER+ZUOA9k///lP3HPPPbBYLFi2bNlF+3/961+7rTAiIiIif9FhICstLQUAHDt2rFuKISIiIvJHHQayJ598EgDw6quvdksxRERERP6ow0D206kufurf//53lxZDRERE5I86DGTz5s3rrjqIiIiI/FaHgSwiIgKpqak4ePBgd9VDRERE5Hc6DGRLly7FBx98gCeeeOKifTKZDOvWrXNbYeRbrDYHSisNOFFpAASg1wUgPCQAel0AwnQBkMtkUpdIREQkmQ4D2QcffAAAXDycrllVvRlHTjXidLURDqdwba+sN7u+DtWqMXxgLCLDgqQokYiISHKdWsvSbDbjvffew5YtW6BSqTBy5Eg8+uijUKvV7q6PvNixM43YVlgFAAgJViO1ZwhSeoZArVKgwWBBvaEV1fUtOFlpwOrtp9A/WY/re0dCqZBLXDkREVH36lQge+mll+B0OvHss89CCIG8vDwsXLgQCxYscHd95KWKTjVg56FqBKgUGJXZEzHhQZBdcFsyWh+EaH0Q0hP0SKszY2thJQ6eaMDpKiNGXN8DkaHsLSMiIv/RqUB26NChdlNc3HDDDbjnnnvcVhR5t0Mn67G7qAaBagXGDu0FvS6gw+NjIzS4a3gSCo7V4nBpA77feRpjh/ZCFG9hEhGRn+jUvaHQ0FA0Nja6XpvNZuh0OrcVRd6rsKQOu4tqEBSgwLhhVw5j56iUcgztF41RmT3hcAis230G9c2tbq6WiIjIM3TYQ7Zw4cK2g5RKTJo0CbfffjvkcjnWr1+P3r17d0uB5D2qGszYc7QWmkAlbh/aCyHBVz/GMDFWh+EZsdi8vxJrdp3BuBt6IUzbuVBHRETkrToMZGFhYQCAIUOGYMiQIa7tEyZMcG9V5HUcTie2nx3AP+r6ntcUxs5J6RkKu0Ng+8EqrNl1GuOGJfys8xEREXm6DgPZrFmzLrvPbDZfdh/5n4Ml9WgyWdE3IQxR+p8/9iutVxgcDoFdRdVYv6cMv7gpESoln74kIiLf1KlB/WvXrsXbb78Ns9kMIQScTicaGxuxd+9ed9dHXqDJaMX+4noEBSgwqE9kl523X5IeplYbDp1swPaDlRiR0aPdk5pERES+olOBbOnSpfj973+PL7/8Eo8++ijWrl2L4OBgd9dGXkAIge2HKuEUAsP6xUCtUnTp+bPSolDd0IITFQbEhmvQp1dYl56fiIjIE3TqHlBQUBDGjx+PzMxMBAQEYP78+di4caObSyNvUFzWjKr6FsRHa5EQo+3y88vlMozM7Am1So6dh6vRYOCTl0RE5Hs6FcgCAgJgtVqRkJCAw4cPQy6X89YRwWZ3Iv9IDZQKGW7oF+22vxPaIBWGX9cDDqfAD3vLYbM73fI5REREUulUILvlllvwu9/9DiNHjsTHH3+MJ554Anq93t21kYc7dqYRFpsDA5LDERykcutn9YrWon+SHs1mG3YeqnLrZxEREXW3To0he+yxx3D33XcjJiYG7777Lnbt2sWpL/yc0ylw6GQDlAoZ+iZ0TzjPSotCVb0ZxeXN2F9ci4zUrnuAgIiISEqdnkeguLgYS5YswerVq9GvXz9ERES4sy7ycCcrm2FutaN3XCgC1V07kP9y5HIZbr4uFjIZ8Ml/jqDFYu+WzyUiInK3TgWy999/H6+++ioCAwMhl8sxb948fP755+6ujTyUEAKFJfWQyYD+SeHd+tl6XSCuS4lAg8GCv28s7tbPJiIicpdO3bL85ptvkJeXB6227Sm66dOnIycnBw8++KBbiyPPVF5rRqPRiqQeOmg17h07dinXpUbgVJUBG/eWQa2UIzZC06n3jc6Mc3NlRERE16bTT1leOO9YaGgoAgK4vqC/OniiHgAwILl7e8fOUchluHlgLGQAth2shN3Bpy6JiMi7ddhD9v333wMAkpOT8V//9V+YPHkyFAoFvv76awwcOLBbCiTPUtvUisp6M3pEaBAREihZHZFhQeiXpMehkw0oOFaLIenRktVCRET0c3UYyHJzc9u9XrZsmevruro691REHk3q3rELZfaJxKkqIw6XNiA1LhR6HXttiYjIO11VILPb7RBCQKXq/nFDJD1zqx2nKg3Q6wLQo5PjttxJqZBjWL9orN9Thp2HqnD7sF6csJiIiLxSp8aQ1dXV4be//S0yMzORkZGBhx56CFVVnJzT35RUNEMA6NMr1GOCT3y0Fr2itahqaMGJimapyyEiIromnQpkCxYsQGZmJrZu3YqtW7diyJAhmD9/vptLI08ihEBxWRPkMhmSY0OkLqedoenRUMhl2F1UA6vNIXU5REREV61TgezkyZOYNWsWQkJCoNfr8eSTT+LUqVPuro08SF2zBU1GK3pFByOgmyaC7SytRoXrUiPQanWg4Fit1OUQERFdtU4FMrvdDovF4nrd0tJyxVtWTqcTL774Ih544AFMmzYNpaWl7fbn5eVh0qRJmDJlCjZs2NBu365duzBq1KjOtoG6QXFZEwAgNS5U4koubUCyHjqNCkdONaK+uVXqcoiIiK5KpyaGHT9+PB555BFMmjQJMpkMK1euxLhx4zp8z9q1a2G1WrFixQoUFBRg8eLFeO+99wAANTU1yM3NxcqVK2GxWJCTk4Phw4dDrVajoqICf/vb32C3c1kcT+FwOnGiohmBagV6RgZf+Q0SUMjluKF/DNbuPoMdh6pwxw0JHjPOjYiI6Eo61UM2c+ZM3H///diyZQs2bdqESZMmYdasWR2+Jz8/H9nZ2QCAzMxMFBYWuvbt378fgwYNglqthk6nQ0JCAoqKimCxWPCnP/2J49M8zJlqE6w2J1J6hkAu99yQ0zMyGAkxWtQ0tqKknAP8iYjIe3Sqh+zhhx/GJ598gvvuu6/TJzYaja6llgBAoVDAbrdDqVTCaDRCp9O59gUHB8NoNGLBggWYPn06YmJiOv05er0GSmXXjGmKitJd+SAfdqn267SBKK2qAABk9ImCTivdZLCdMSqrF774rgh7j9Wif0ok1Krzfzc6ur689v7bfn9uO+Df7ffntgNsv6e1v1OBzGAwwGw2Q6Pp/NxTWq0WJpPJ9drpdEKpVF5yn8lkgkqlwu7du3Hq1Cn85S9/QVNTE2bPno3//d//7fBzGhrMna6pI1FROtTUGLrkXN7ocu2vrjOitLIZ4SEBUCtkMBg9e3yWDMDAlHDsO16HLfvK2s3gf7nry2vvv+3357YD/t1+f247wPZL2f7LBcFOBbKgoCCMGTMGffv2bRfK3n///cu+JysrCxs2bMD48eNRUFCAtLQ0176MjAy8+eabsFgssFqtKC4uRkZGBr777jvXMcOHD79iGCP3O1HeDCE8dzD/pQxIDkdxWTMOlzagT3woQrWcwZ+IiDzbFQPZ0aNHceutt2LEiBGIjY3t9InHjh2LLVu2YOrUqRBCYNGiRVi2bBkSEhJw6623Ytq0acjJyYEQArNnz+Zi5R6quLwZchmQ3MOzunY7olTIMSQ9Chv3lmPn4WrcNiSeA/yJiMijdRjIVq5ciSVLliAxMRGnTp3Ca6+95hqofyVyuRwLFixoty01NdX19ZQpUzBlypTLvn/Lli2d+hxyn/JaExoMFsRHaxGo7lRnqsfoFa1FjwgNKurMOF1tREKM9wRKIiLyPx0+ZZmbm4t///vf+Pvf/473338f//d//9dddZEHyD9SDQBIitVe4UjPI5PJMKxfNGQyYHdRDewOp9QlERERXdYVp70498TjoEGD0NDQ4PaCyHPkH6mBXAbER3lfIAOAUG0A+iXqYWyx4eCJeqnLISIiuqwOA9lPx90oFJ61ZA65T3WDGaeqjegRGdxu6ghvk9E7AkEBChSW1KO2qUXqcoiIiC6pUxPDnsOB0f4j/0gNACDRy8deqZUKZKVFweEUWLH+uNTlEBERXVKHI7WPHDmCrKws1+vW1lZkZWVBCAGZTIY9e/a4vUCSxu4j1ZDLZIiP9s7blRdK6RmCo6cbkX+kBodO1qN/UrjUJREREbXTYSBbs2ZNd9VBHqS2qQUnKgwYkKRHoNp7b1ee0zbAPwb/b1spvlh7DPN/PRRKxVV1DhMREblVh4EsLi6uu+ogD7Ln7O3KwX2jr3Ck94gIDcTIzJ74oaAc6/eU4fahvaQuiYiIyIXdBHSR3UdrIJMBg9KipC6lS00amYLgQCX+ubkETSar1OUQERG5MJBROw0GC46faUJafBhCg9VSl9OldBo1JmanoMXiwMqNxVKXQ0RE5MJARu3sOdp2u/LCRbl9yehBPREfpcXmAxUoLm+SuhwiIiIADGT0E+dm58/ysduV5yjkcjw4tg8A4Is1R+EUQuKKiIiIGMjoAsYWG46cbkRqXAj0Ot9d7L1vgh439I/BiQoDNu+vkLocIiIiBjI6b39xLYQAMntHSl2K200Z0xsBKgVW/lAMY4tN6nKIiMjPMZCRS8HxOgD+Ecj0ugBMuDkRBrMNn68+LHU5RETk5xjICABgsztRWFKHyNBA9IwMlrqcbnH70ATEhGvw7dYTKClvlrocIiLyYwxkBAA4WFKLVqsDmb0j/WbNUpVSjofH9YUQwCf/KYLd4ZS6JCIi8lMMZAQA2HmoCgBwfR/fv115ofREPcYOS8DpaiPW7D4tdTlEROSnOlw6ifyDEAI7D1YiKECBvr3CpC7HbTYWlF1ye0KsDoFqBVb9UAK7wwmdpm1C3NGZXDqMiIi6B3vICOW1JlTVmzEgOcIvF90OVCsxJD0aDqfAjkNVEJybjIiIupn/ffelixQcrwUAZPaOkLgS6ST30KFHhAbltWacqDBIXQ4REfkZBjLCvuN1kMuAjFT/Gj92IZlMhhsHxEAhl2HX4Wq0WOxSl0RERH6EgczPNZutKC5rQnpSOLRBKqnLkZROo0ZW3yhYbA5sO8hbl0RE1H0YyPzcgeI6CADD+sdKXYpHSE8IQ2y4BmeqjdhaWCl1OURE5CcYyPzcufFjwwYwkAFtty5vHhgLpUKGL9YeQ31zq9QlERGRH2Ag82M2uxOFJ+oRHRaE+Git1OV4DK1GhSHp0Wix2LFsdRFvXRIRkdsxkPmxI6cbYLE6kNnHf2bn76w+8aEYmBKOgyfqsbGgXOpyiIjIxzGQ+bF9x9oWE7/eDxYTv1oymQy/vrMfggOVWL7uGM5UG6UuiYiIfBgDmZ8SQqDgeC2CApToEx8qdTkeSa8LwPTx/WCzO/HePwvRauVUGERE5B4MZH6qrMaEuuZWXJcS7pez83fWoLQojB3SCxV1Znz+/VGpyyEiIh/F78R+6vzs/LxdeSWTx6QiKVaHLYWV2HKgQupyiIjIBzGQ+al9x2shl8lwXar/LpfUWUqFHI9NHIigAAVyvz+CslqT1CUREZGPYSDzQ80mK0rKm9EnPhTBgf49O39nRYcF4dd39oPV5sQ7qw7A1GqTuiQiIvIhDGR+aF9xLQT4dOXVGpIejTtuSEBVvRnv/qMQdodT6pKIiMhHMJD5oX3H26a7yOzDQHa17h+ViszekThc2oAv1h7jpLFERNQlGMj8jM3uwMET9YgJ1yA2XCN1OV5HLpfhd3f3R3yUFhv3lmFd/hmpSyLuJcsxAAAgAElEQVQiIh/AQOZnik41wmJzILM3B/Nfq0C1Ek/dn4GQYDW+XHcM+4vrpC6JiIi8nFLqAqh7cbqLzttYUNbh/uHXxeK7nafx55X7ceuQeMSGazA6M66bqnO/K7X/Unyp/URE3Yk9ZH5ECIF9x2sRHKhEb87O/7NFhQVh9KCeEEJgff4ZVDeYpS6JiIi8FAOZHzldbUR9swXXpURAIeel7wrxUVqMzOwJh1Ng3e4ylJQ3S10SERF5IX5X9iP7zt6u5HQXXSshRofsjB6wO5x4Y0UBSisNUpdERERehoHMjxQcr4NCLsN1KeFSl+JzknqEYHhGLFosdiz+Yg8OlHCgPxERdR4DmZ9oMlpwoqJtdn4NZ+d3i5SeoXhs4kA4HAJv/X3/NQ2KJyIi/8RA5if2nZ2agU9XutfQ9Gg898tB0AQq8el/juDvG47DycljiYjoChjI/IRr/Bhn53e73vGheOGhwYgJ12D1jlP481f70WyySl0WERF5MAYyP2CzO3DwZD16RGgQo+fs/N0hWq/Bf08bjP5JeuwrrsOLH+1wzQFHRET0UwxkfuBwaQOsNiefruxm2iAVnn4gE1Nv6Q2zxY63v9qPT/9TBIvVIXVpRETkYThTvx8oOM7xY1KRy2S4fVgC+ieF48N/H8TGgnIUHK/FvdkpGH5dD8jlsms679U+MMAZ9ImIPBt7yHzchbPzp8aFSF2O34qP1mLew0Mw4eYkmFrtWLa6CPOX7cSBkjoIDvonIvJ77CHzcaeqjGgwWHDTgBjOzi8xlVKBSSNTMDqzJ77+8QS2HKjA/+btQ0rPENySFYeh6dFQKRVSl0lERBJgIPNxnJ3f84SHBGL6L/ph7NBe+MemEuw7Xou/ljdj+brjyL6+B24aEIu4yGDIZNd2O5OIiLwPA5mPKzheC4VchoHJEVKXQj/RK1qLJ+/PQE1jCzYWlOHHfRVYvf0UVm8/hcjQQFzfOxKZvSPRJz4UahV7zoiIfJnbApnT6cT8+fNx5MgRqNVqLFy4EImJia79eXl5WL58OZRKJR5//HGMGTMG5eXleP755+FwOCCEwIIFC5CSkuKuEn1efXMrTlYa0D9JD00gs7enigoLwuTRvTFxRDL2HK3F3mM1OFBSh3X5Z7Au/wwUchniooKR0jMUyT10iI/Swmp3QM3bm0REPsNt36XXrl0Lq9WKFStWoKCgAIsXL8Z7770HAKipqUFubi5WrlwJi8WCnJwcDB8+HG+99RZ+9atf4bbbbsOPP/6IN954A++88467SvR5+UdqAACD+0ZLXAl1hkqpwA39Y3BD/xjYHU4cPd2I/cV1KC5rQmmVEaeqjNi49/zxQQEKhGjU0GpUCA5UIThQieCgtt81gSqolBwzSETkLdwWyPLz85GdnQ0AyMzMRGFhoWvf/v37MWjQIKjVaqjVaiQkJKCoqAhz5syBTqcDADgcDgQEBLirPL+Qf6QaMgBZnJ2/21zL+pWXmpJCqZCjf1I4+ie1LQRvdzhxpsaIE+XNKK8z43BpPZpNNlQ1tKCqoeWS5w1QKRAcpERwoApl1SaEhwYgIiQQMXoNYiM0COBtUCIij+G2QGY0GqHVal2vFQoF7HY7lEoljEajK3gBQHBwMIxGI8LD2775lJSUYMmSJfjLX/5yxc/R6zVQdtGtm6go3ZUP8hINza04VtaE/ikR6J3cuUB2qfbrtIFdXZpHkrKdnf171yM2FEOvawtv/9l2EkBbUDO22GA0W2E022Aw22BsscJw9nWzyYb6ZgtOVxvbnUsma1tNoFeMDqlxoUhL1KNvgh6h2vM/BF3Ln4k3/hvyxpq7kj+335/bDrD9ntZ+twUyrVYLk8nkeu10OqFUKi+5z2QyuQLa9u3b8dJLL2Hp0qWdGj/W0GDuknqjonSoqTF0ybk8wYY9ZyAEkJEc3ql2Xa79BmOrO8rzKDptoKTtvJa/dxfWqwAQqlEhVKO66DghBCw2J/ol6FHf3Ira5lZU1ptRUWtCeZ0Zuw9XYffhKtfxUWGBSE/Q47qUCNQbWq/6YQJv+zfka//ur5Y/t9+f2w6w/VK2/3JB0G2BLCsrCxs2bMD48eNRUFCAtLQ0176MjAy8+eabsFgssFqtKC4uRlpaGrZv345XXnkFf/3rXxEXx5nFf47drvFjURJXQlKSyWQIVCuQGKtDYuzF/wkYW2yoN9uw93AVSsqbUVLehB/3V+DH/RWQyYDI0CAkxmiR1COED4YQEbmR2/6HHTt2LLZs2YKpU6dCCIFFixZh2bJlSEhIwK233opp06YhJycHQgjMnj0bAQEBWLRoEWw2G+bOnQsASE5OxoIFC9xVos8ymK04cqoRKT1DEB7iH7cc6dpog1RITghHQkTbovNOp8DJSgMKS+qwpbACtY0tqGlswe4jNYgN1yC5ZwiSYnV8YICIqIu5LZDJ5fKLwlRqaqrr6ylTpmDKlCnt9v/rX/9yVzl+Ze+xWjiFYO8YXTW5XIaUniFI6RmCEK0arVY7TlYacKLcgMp6Myrrzdh9uBqpcSFIT9QjJFgtdclERD6B9yB8EKe7oK4SqFYiPUGP9AQ9DGYrTpQ34+jpJhSdakTRqUb0jNRgQHI4YsM117SyQFc9lUpE5O0YyHyMudWGQyfrkRCjRXRYkNTlkA/RadTI6B2JgSkROFVtRFFpA8przSivNSMqLBAZqZEQQnDJJyKia8BA5mMKjtfC4RTsHSO3kctlSIrVISlWh7qmVuwvrsPpaiPW5Z9BSXkzJo1MwYDkcKnLJCLyKgxkPubc7cohHD9G3SAiNBBjsuJQ39wWzE5UNOP1FQUYkByOyaNTkRDjWfP8EBF5KgYyH2JuteFAST16RgajR0Sw1OVQJ13LOCpPEx4SiNGD4pDSIwR5G47j4Il6HDpRj5sHxmLSqFTodVx1g4ioIwxkPmT3kRrYHU7c2D9G6lLITyXE6PCHBzJx8EQ98jYcx5bCSuw+UoN7RiTjtiHxUCo4XQYR0aUwkPmQrQcqAAA3DYiVuBLyNB31wnX1SgUymQwDUyLQPykcmw9U4KuNxcjbcBybD1TgV2PTkJ6o77LPIiLyFfxx1UfUNrbg6JkmpCeEISKUk8GS9ORyGUZe3xOLfncjRmf2REWtCUu/3IsP/3UQjUaL1OUREXkU9pD5iG0HKwGwd4w8jzZIhYfuSEf29T2R+90RbD9UhYLjtZiYnQKlQga5nNNkEBGxh8wHCCGw9WAVVEo5hqRzugvyTMk9QvDCQ0Pw0B19oZDLsHzdMXyz9SSqGsxSl0ZEJDkGMh9wosKAqnozBvWJRFAAOz3Jc8nlMozOjMOi392Ikdf3RKPRiu92nMbWA5VotdqlLo+ISDL87u0Dtha2Dea/eSBvV5J30GnUeOTOdAQHKbH9YBWOlzXhVLUBg/tGoXdcKGf7JyK/wx4yL2d3OLHzcDVCNCrOjk5eJyosCL+4KRFD0qPgdApsK6zCf3acQoOh6576JCLyBgxkXu5ASR2MLTYM6x8DhZyXk7yPXC5D/6RwTMxORmKsDjWNrfhmayl2F1XDZndKXR4RUbfgLUsvt62w7enK4QN7SFwJ0c9bdUATqMKozJ4oqzFh5+EqHDrZgJMVBgxJj0JirI63MYnIp7FLxYs1m6woOF6LnpHBSIjRSl0OUZeIiwrGXcOTkJEagVarA5v2VeC7nadR18zbmETkuxjIvNgP+8phdwiMGRTH3gPyKUqFHJl9InFPdhJ6RWtR3dCCb7eWYmthJZo4qSwR+SAGMi/lcDqxcW8ZAtQKPl1JPkunUWNMVhxuGxKPMK0ax880Yc4H27BqUwnMrZwmg4h8BwOZl9p7tBYNBgtGDOzBucfI5/WMDMaEm5NwY/8YBAUo8c3Wk5j7wTZ8t/MUbHaH1OUREf1sDGReal3+GQDALYPjJK6EqHvI5TKkJYRh8e9uwqSRKXA4nVix/jiee28b/rPjFCeWJSKvxq4VL3S62ogjpxsxIEmPHhHBUpdD1K0C1ApMuDkJowfFYfWOUqzfU4a8Dcfx/7aXYuzQXrglKw7BgSqpyyQiuioMZF7ofO9YvMSVEElHG6TC5NG9cecNiVi7+zTW7j6Df2wqwbfbTuLmAbG4dUgvxEXyBxYi8g4MZF7G1GrD9oOViAwNxPWpkVKXQyQ5bZAKE7NTMG5YAn4oKMe6/DPYWFCOjQXl6J+kx+jMOFzfOxIqJUdoEJHnYiDzMj/uq4DV7sQtWfGQyznVBdE5QQFK3HFDAsYOjUfBsTqsyz+NQycbcOhkA4IDlbhxQCxGXNcDibG6Tp3vaie5HZ3J8ZxEdO0YyLyI3eHE+j1noFbKMSKDM/MTXYpCLsfgvlEY3DcKZTVGbD5QgW2FlViXfwbr8s+gR4QGQ9OjMSQ9GpGRnFCZiDwDA5kX2VpYidqmVozJioM2iIOWia4kLkqLB27pg/tGpeJASR22HqjE/pI6/GvLSfxry0n0itFiYFI4BqZEoE98KJQK3tYkImkwkHkJm92Jf285AZVSjgk3JUldDpFXUSrkGNQnCoP6RKHVase+43XYXVSNAyV1OF1lxOodpxCgVqBfgh7XpbQFNCKi7sRA5iU27StHXbMFtw/tBb0uQOpyiLxWoFqJG/rH4Ib+MdCFBmHLnjMoLKnDgRP1KDhei4LjtQCAkGA14iKDERMehGi9BoFqhcSVE5EvYyDzAlabA99sO4kAlQLjb0yUuhwinxGoViIjNQIZqW09YtWNLSgsqUNhST0KT9ThcGkDDpc2AADCtGpE6zWI0QchJjwIGs51RkRdiIHMC2zYW4YmoxW/uCkRIcFqqcsh8jqXe2JSpw2EwdjabptcLkNG7wgMSNGjpqEVVQ1mVDW0oLaxBY3GRhw93QigbbqNaH0QosKCEBkWCIfTCYWcY9CI6NowkHm4Vqsd324rRVCAAuOGJUhdDpHfUMjliI3QIDZCAwBwOgXqmltR1dCC6nozqhtaUFLejJLyZgDAmp2nkRirQ0rPEKT0DEVKjxCEhwRAJuP0NER0ZQxkHm5d/hkYW2y4Z0Qyn6wkkpBcLkNUWFuPGJLDIYRAo9GK2sYW1Da1osXiwPGyJhw70wTgNAAgNFh9NqCFIKVHCJJ6hCAo4Of9t8v50Yh8EwOZB2s0WvD/tp9CcKASY4f0krocIrqATCaDXhcAvS4AfXq1BZ9Wqx2llQZXz1lJRTP2HqvF3mNtDwrIAESHa5AYo0WvaC0SYnRIiNEhlEMRiPweA5mHEkIg97sjaLHYMe32NGgCeamIgKvvIeouF9YVFKjEgJRwDEgJh7nVhprGVtQ2taK2qQUNza2oqjdj5+Fq1/Ghweqz4UyLuMhg9IwMRo8IDVRKPtlJ5C/4Xd5D5R+pwd5jtUjrFYZRg3jLgchbaQJVSIxVuZZsEkLA1GJHvaEVIRo1TlUZcaragAMldThQUud6n0wGRIUFoWdEW0A7F9TsDicnsCXyQQxkHsjYYsNn3x+BSinHI3emQ85BwUQ+QyaTQatRQatRtRvfZTBbcbraiPJaE8rrzCivMaKs1tRubrRztEEqhGnVCNUGICRYjZBgFUKD1QhQKfgQAZGXYiDzQCvWHUOz2YbJo1MRG66Ruhwi6gY6jRr9k8LRPynctU0IAYPZhvJaE8pqTSivM+HQyXo0Ga04U2PCmRpTu3OolfKzAe3sL40Kp3qEIEavQQAntiXyaAxkHqawpA5bCiuRGKPD7cM4kJ/In8lkMle4Sk/UAzg/Vq3VakeT0YpmkxXNZiuaTTY0m6yob24br3bOpn0VAAC9LgCx4RrEhmsQE65BbHgQ+slkkHP+NCKPwEDmQZqMFixbXQSFXIZfj0/nf5JEdFmBaiUCw5WI+UkvutMpYGq1ocl0NqydDWrNZmu7lQfOkcvaeud0Z3vUQoPVGHl9T8SGaxASrOYtUKJuwkDmISw2B95euR8NBgvuG5WChBid1CURkReSy2VtAUujBqLa77PZnTCYz/Wq2dBicaCuqQVNJiuaTFbXcdsOVgEAggIUiNFf2KvW9itaH/Sz51Mjovb4L8oDOIXAR98cwokKA4YPjOV6lUR+orun8FAp5QgPCUR4SCCA80tHCSFgsTnQbLKiyWRDmFaNqvoWVNabcabGiJOVhovOFaZVu4La+dDWNnFuZ58C5SS3ROcxkHmAf2wqwe4jNUjrFYaH70znLQIi6lYymaztFqhaiWh9++BzbsmoynozKuvNqLrg96JTjSg61djuXHKZDJFhgW0BTd82Vi06XINYvQb6kAA+NU50GQxkEtu8vwLfbitFtD4IsyZdx/mFiEhyl+u5UinliI/WIj5aCwCwO5wwmNvGqEWGBrb1qjW0hbX9xXUA6i56f4w+yHX7s8FgcU3bwSk7yN8xkEloze7TWL72GIIDlfj95Ou5ViUReRWlQu5aPuqntxNNrTZU1bec71FrMLsC20+n6wAAtUqOEI0aYdoAhOnaftfrAhCoZlAj/8BAJgGnU2D5+mNYu/sMQoPVeGpyBucbIyKv1tF4MH1IAPQhAUhP1EMIgRaL4+xUHecfMDBcYsoOAAhQKRCmVSNMFwAIIC6qbdUCTSB/gCXfwkDWzSxWBz7410EUHK9FXGQwnpqcgcjQIKnLIiLqFjKZDJpAJTSByot+EHU6BZrNVjQaLGg0WtFgsKDRaEFVQwuqGlpw5ILxauEhAYiLbFuk/dyv2HAN5HL2ppF3YiDrRsXlTfhk9RGcqTGiX6IeM+8dyJ/yiIjOkstlbbcstQHtttsdTjRdENAajRY0GKwXrf+pkMsQdvYWariurVfu7puTOUUHeQX+Le0GxhYbVv5QjE0F5RAARg+KQ85tfTiAn4ioE5QKOSJCAxERGthue6vVgUaDBfWGVjQYLKhvtqCh2YK6C257frfjNCJDA5EQo2vXmxYZqe3uZhB1iIHMjSw2B7YVVuIfP5bAYLYhLjIY08b1RVqvMKlLIyLyeoFqBWIjNIiNOH/r0+kUaDJZ0WBobQtohrZfe47WYM/RGtdxapXc9eBAeEgA9LpAhGnVUCrknO+MJMFA5gZVDWZs2FOGLQcqYGq1Q62SY/KYVIwd0ou9YkREbiSXy1xPfqb0bNt27kGCBkMr6g1tvWhNJitqGlpQ3dDieq8MQHCQCnuP1qJHxPmVCXpEcBkpcj8Gsi7gFAKnq4w4eLIehSV1rokSQzQqTLg5EWMGxUOvC7jCWYiIyB3OP0igRVxU261KnTYQDU3mtvFozRbUGyxoNLQFtZ+OTQPOLyMVefbWaUTI2V9nX2sClAxs9LO4LZA5nU7Mnz8fR44cgVqtxsKFC5GYeH5JoLy8PCxfvhxKpRKPP/44xowZg/r6ejzzzDNobW1FdHQ0Xn31VQQFedYTiA6nE9UNLSirMeFMjRFlNSYcPdMIg9nmOqZPfCjGZMVhcFo0VEr2iBEReSKlQo7I0KCLnnQflh6NinozKuva5lCrrDOjooNlpAAgQK1AREggQjSqs2uJtv1+4WutRo0gtQKBagUC1Uo+EUrtuC2QrV27FlarFStWrEBBQQEWL16M9957DwBQU1OD3NxcrFy5EhaLBTk5ORg+fDjeffddTJgwAZMmTcKHH36IFStW4JFHHnFXiZ2y/WAldhVVt41DMFrQbLJCiPbHhGrVGD4wFgOSw9E/KRwhwWppiiUiop9tZ1G16+tzPWADUsJdtz5NrTYYW2wwtdpharEhUKVAXbMFDYZWlNdePOnt5aiVcgSqFQg4G9AC1AqoFHIoFDIo5Wd/V8ihlMugOLv9XISTQYZzL1yxTnbBPgAyGXCmxnjR58pkgFqlhNXmOP+2s6dLiNFBJjt/lgs7/WQymevYc6/lsrblss59LZPJIJfLIJOh/TZZ27Zz++SubWePkXd8rnPbz3997lwXvg9wirZb1E4BCKeAUwgIAdfvbfsEqg1W1NWbYLM7YLU5YbM7EaZVo19SeKevX1dzWyDLz89HdnY2ACAzMxOFhYWuffv378egQYOgVquhVquRkJCAoqIi5OfnY8aMGQCAkSNH4o033pA8kG3aV46iU41nZ6RWo09cKCLDghAfpUVcVDDio7QI03JsARGRr7twDrWosPO9ahc+BGB3OGFssbUtKWW2wmC2wmC2wWC2wmi2odXqOPvLjlarAxZb2+vapha0Wh0X/cDf3Q6U1EtbgIRkMuDd2aMQoFZI8vluC2RGoxFa7fnHihUKBex2O5RKJYxGI3Q6nWtfcHAwjEZju+3BwcEwGC7dNXyhqCjdFY/prEud63+eGtVl5/d0l2r/5LHpElRCRETkX9w2wEmr1cJkOt9163Q6oVQqL7nPZDJBp9O1224ymRASEuKu8oiIiIg8htsCWVZWFjZt2gQAKCgoQFpammtfRkYG8vPzYbFYYDAYUFxcjLS0NGRlZeGHH34AAGzatAmDBw92V3lEREREHkMmhHvuWJ97yvLo0aMQQmDRokXYtGkTEhIScOuttyIvLw8rVqyAEAIzZszAuHHjUFtbizlz5sBkMkGv1+P111+HRsNFt4mIiMi3uS2QEREREVHncJIsIiIiIokxkBERERFJzK+XTtq3bx9ee+015ObmorS0FHPnzoVMJkOfPn3wpz/9CXK57+VVm82G559/HmVlZbBarXj88cfRu3dvv2g7ADgcDrzwwgs4ceIEFAoFXn31VQgh/Kb9AFBXV4dJkybhb3/7G5RKpV+1feLEia6pdeLj4/HAAw/glVdegUKhwIgRIzBr1iyJK3SvDz74AOvXr4fNZsMvf/lLDBs2zC+u/6pVq/CPf/wDAGCxWHD48GHk5ub6zbW32WyYO3cuysrKIJfL8fLLL/vNv32r1Yo//vGPOH36NLRaLV588UU0NjZ65rUXfurDDz8UEyZMEJMnTxZCCDFjxgyxfft2IYQQ8+bNE99//72U5bnNV199JRYuXCiEEKK+vl6MGjXKb9ouhBBr1qwRc+fOFUIIsX37dvHYY4/5VfutVqv4r//6L3H77beL48eP+1XbW1tbxT333NNu29133y1KS0uF0+kUv/3tb0VhYaFE1bnf9u3bxYwZM4TD4RBGo1G8/fbbfnX9z5k/f75Yvny5X137NWvWiCeffFIIIcTmzZvFrFmz/Oba5+bmihdeeEEIIURxcbGYPn26x15734vDnZSQkIA///nPrtcHDx7EsGHDALStErB161apSnOrO+64A0899ZTrtUKh8Ju2A8Btt92Gl19+GQBQXl6OyMhIv2r/kiVLMHXqVERHRwPwn7/3AFBUVISWlhZMnz4dDz30EHbt2gWr1YqEhATIZDKMGDEC27Ztk7pMt9m8eTPS0tIwc+ZMPPbYYxg9erRfXX8AOHDgAI4fP45f/OIXfnXtk5OT4XA44HQ6YTQaoVQq/ebaHz9+HCNHjgQApKSk4MCBAx577f02kI0bN841US3Qtr7VueWPOrtKgDcKDg6GVquF0WjEk08+id///vd+0/ZzlEol5syZg5dffhnjxo3zm/avWrUK4eHhriXNAP/5ew8AgYGB+M1vfoOPPvoIL730Ev74xz8iKOj88je+3v6GhgYUFhbirbfewksvvYRnnnnGr64/0HbLdubMmRetJOPrbddoNCgrK8Odd96JefPmYdq0aX5z7fv164cNGzZACIGCggIYDIZ202l5Utv9egzZhS68d+7rqwRUVFRg5syZyMnJwV133YX/+Z//ce3z9bafs2TJEjzzzDOYMmUKLBaLa7svt3/lypWQyWTYtm0bDh8+jDlz5qC+/vy6db7cdqCtlyAxMREymQzJycnQ6XRobGx07ff19oeFhSElJQVqtRopKSkICAhAZWWla7+vt7+5uRklJSW48cYbYTQaL1otxpfb/vHHH2PEiBH4wx/+gIqKCjz88MOw2Wyu/b7c/vvuuw/FxcV46KGHkJWVhfT0dLS0tLj2e1Lb/baH7Kf69++PHTt2AGhbJWDIkCESV+QetbW1mD59Op599lncf//9APyn7QDw9ddf44MPPgAABAUFQSaTYeDAgX7R/s8//xyfffYZcnNz0a9fPyxZsgQjR470i7YDwFdffYXFixcDAKqqqtDS0gKNRoNTp05BCIHNmzf7dPsHDx6MH3/8EUIIV/tvuukmv7n+u3btws033wygbfk+lUrlN9c+JCTE9TBLaGgo7Ha73/y/f+DAAQwePBi5ubm47bbbkJSU5LHX3q8nhj1z5gyefvpp5OXl4cSJE5g3bx5sNhtSUlKwcOFCKBTSrPjuTgsXLsTq1auRkpLi2vbf//3fWLhwoc+3HQDMZjP++Mc/ora2Fna7HY8++ihSU1P94tpfaNq0aZg/fz7kcrnftP3c01bl5eWQyWR45plnIJfLsWjRIjgcDowYMQKzZ8+Wuky3Wrp0KXbs2AEhBGbPno34+Hi/uf5//etfoVQq8cgjjwBoW9LPX669yWTC888/j5qaGthsNjz00EMYOHCgX1z7+vp6PP3002hpaYFOp8Mrr7yCiooKj7z2fh3IiIiIiDwBb1kSERERSYyBjIiIiEhiDGREREREEmMgIyIiIpIYAxkRERGRxBjIiMhjTJs2DR9++OFF2//2t7/h8ccf7/C9c+fOxUcffeSu0lyMRiOmTp2KX/ziF/j+++8veUxubi769u2LgoICt9dDRL6BgYyIPEZOTg5Wrlx50fa8vDw8+OCDElR0scOHD6Ourg7ffvstbr/99kses3z5ctx111345JNPurk6IvJWDGRE5DHGjh0Ls9mM3bt3u7bt3LkTQggMHz4cTqcTCxcuxOTJkzF+/HjceeedyM/Pv+g8ffv2bbcs1IWv169fj8mTJ2PixImYOnUq9u7de8la1q5di4kTJ+Luu+/GL3/5S+zfvx8lJSV4/vnnUVVVhXvuuQetra0XvW/Hjh1oamrCs88+i3Xr1qGiosK1r7S0FA8++CAmTBHUsfYAAAQvSURBVJiAX//613jkkUewatUqAMCePXuQk5ODe++9F/fddx82bNhwbX+IROSVuJYlEXkMpfL/t3c/IW1sURzHvyMWBEFpwAYkgjQBXQhaXZjoSoS6kEShECTd6KIU1E0rCtKC/xe6aelGqbgJIv4p9J9IkWoVDGnpRtRNKQE1C4muSkWwzUy6KB2eWEt55b3oe7/ParjDPXPnrg5n7nAyCQaDPHnyxG5nMjMzQygUwjAM1tfX2d/fZ2ZmhoyMDB4/fsz4+DgVFRW/FX97e5sHDx4QDoe5fPkyHz9+pKWlhcXFxRMNh2OxGD09PUxPT1NQUEA0GqW1tZVXr14xODjIwMAAz58//+kzpqam8Pv9OJ1OvF4vk5OTdHZ2AtDV1UVDQwOhUIhYLMaNGzcIBAJ8+vSJ7u5uJiYmcLlcJBIJgsEgRUVF5Ofn/+GuishFoIRMRM6VYDBIfX09h4eHJJNJ1tbW6O3tBeDatWvk5uYyPT1NPB7n3bt3ZGdn/3bsSCTC/v6+3T4HwDAMdnd3KS4utsfevn2L1+uloKAAAJ/Ph8PhYGtrC8Mwzox/cHDA0tKS/dm1sbGR3t5e2tra+Pr1KxsbG0xOTgLgdrvxer3A9zY+BwcHtLW1nVjXhw8flJCJ/E8oIRORc8XpdFJVVcXCwgJHR0fU1dXZjZFXVlYYGhqipaWF2tparl69yosXL34Z78uXL/a1ZVn4fD4ePnxoj+3t7XHlypUTcyzLOpV4pVIpkskkly5dOvNZs7OzAPYPCJZlcXh4yNOnT2loaLDj/PCjd6Bpmrjdbubm5ux7iUQCh8Pxy3cTkf8OnSETkXPn5s2bvHz5kmfPnp04zB+JRKipqSEUClFSUsLr168xTfPUfIfDwebmJgDz8/P2uM/nIxKJEIvFAFhdXSUQCJw6C+bz+VhbWyMejwMQjUbZ29ujtLT0zDWbpsnc3Bx9fX0sLy+zvLzMysoKt2/fJhwOk52dTXl5uX1mLB6PE41GMQyDsrIydnZ2eP/+PfD9x4G6ujoSicTf2T4RuYBUIRORc6eyspLBwUFyc3MpKiqyx5uamujo6MDv95NMJqmurmZxcRHLsk7Mv3//Pv39/eTk5FBVVUVeXh4AHo+H/v5+7t69SyqVIjMzk9HR0VOfPT0eDz09PbS3t2OaJllZWYyNjdmVup958+YNlmXh9/tPjDc3NxMOh1ldXWV4eJh79+4xNTWF0+nE5XKRlZWFw+Hg0aNHjIyMcHx8TCqVYmRkBJfL9adbKSIXhJH6a/1cRET+MaOjo1y/fh23283nz58JBAKMj4/j8XjSvTQRSTNVyERE/iWFhYXcuXOHjIwMTNPk1q1bSsZEBFCFTERERCTtdKhfREREJM2UkImIiIikmRIyERERkTRTQiYiIiKSZkrIRERERNJMCZmIiIhImn0D5eo2GLrk/TgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xf5ab588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for name in trainFilled.columns:\n",
    "    if name != 'Outcome':\n",
    "        drawHisAndScatter(trainFilled,name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "经过处理过后的特征值的分布还不错。 血压BloodPressure 和BMI 基本满足正态分布。Insulin 出现了两个峰值的情况，大概在150和200，可能是与我们填写的平均值有关系。skinThicness也和insulin 一样出现了双峰值，估计也是与我们填补的平均值有关系。这次调研的大部分人数年龄都在20-30岁之间。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xfb59438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xfb4f5f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xfbd0cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xfe54f60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAEFCAYAAADuT+DpAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzt3Xl8VfWd//HXOXfNvTf7RhIIEBZZA2IArYpWh5/LiHa0FccZp8tM61bUjj8roqJ1q1sZrbZV5zedGbVWx2qrU5dWFERA2SQsEWWH7AtZ783dz/n9cZNLIgkEzcm9yfk8Hw8euffm3ptPQnLe5/s930XRdV1HCCGEaamJLkAIIURiSRAIIYTJSRAIIYTJSRAIIYTJSRAIIYTJWRNdwFfR2NiR6BKEEGLYyc1N7fNxaREIIYTJSRAIIYTJSRAIIYTJSRAIIYTJSRAIIYTJSRAIIYTJSRAIIYTJSRAIIYTJSRAIIZKW39+Z6BJMQYJACJGUPvzwA3784x+ya1dFoksZ8SQIhBBJ6Y03XkPXdTZu/DjRpYx4EgRCiKQkmycOHQkCIURS6g4CRVESXMnIJ0EghEhq0jIwngSBEEKYnASBECKpSYvAeBIEQogkJdcIhooEgRAiScUCQFoExpMgEEIkpe6WgLQIjCdBIIQQJidBIIRIatIiMJ4EgRAiKXVfG5BrBMaTIBBCJDVpERhPgkAIkdSkRWA8CQIhRFKTFoHxJAiEEElN07RElzDiSRAIIZKatAiMJ0EghEhqco3AeBIEQogkJWsNDRWrUW8cDodZunQp1dXVqKrK/fffj9VqZenSpSiKwqRJk7jnnntQVZWnn36a1atXY7VaWbZsGaWlpUaVJYQYNiQAhophQfDhhx8SiUR4+eWXWbduHU888QThcJhbbrmF+fPns3z5ct5//30KCwvZuHEjr776KrW1tSxZsoTXXnvNqLKEEEJ8iWFBMH78eKLRKJqm4fV6sVqtlJeXM2/ePAAWLFjAunXrGD9+PGeddRaKolBYWEg0GqW5uZmsrKx+3zsz04XVajGqdCFEElDVWIvA6bSRm5ua4GpGNsOCwOVyUV1dzUUXXURLSwvPPPMMmzZtivf3ud1uOjo68Hq9ZGRkxF/X/fjxgqClpdOosoUQSULTYtcIgsEIjY0dCa5mZOgvUA0Lgv/6r//irLPO4tZbb6W2tpbvfve7hMPh+Od9Ph9paWl4PB58Pl+vx1NTJf2HSm1tDdFolNGjxyS6FCH6JKOGjGfYqKG0tLT4AT09PZ1IJMK0adPYsGEDAGvWrKGsrIw5c+awdu1aNE2jpqYGTdOO2xoQg+uBB+7mnnuWJroMIfogATBUDGsRfO9732PZsmVcffXVhMNhfvKTnzBjxgzuvvtuVqxYQUlJCRdccAEWi4WysjIWL16MpmksX77cqJJEH/x+f6JLEKIfMmpoqBgWBG63myeffPKYx1988cVjHluyZAlLliwxqhQhxDAm8wiMJxPKBCD9sCJ5ye+m8SQIBADRaDTRJQjRJ2kRGE+CwMR6ruoYDocSWIkQ/ZMWgfEkCEwsEon0eVuIZCItAuNJEJiYBIEYDqRFYDwJAhPTtGiP27L5h0gu0hIYOhIEJtbzTEuCQCQraREYT4LAxHqeccnZlxDmJUFgYqqq9nlbCGEu8tdvYhaLpc/bQghzkSAwMVWVIBBCSBCYmnQNCSFAgsDUel8sll8FIcxK/vqFEMLkJAgEIGO1hTAzCQIT67niqEwoE8lK5rgYT4LAxHouMSHLUItkI63UoSNBYGLRqNbjtiw6J5KTtAiMJ0FgYj27g6RrSCQraRkYT4LAxHRd63Fb/tiEMCsJAhOTRedEMuv+nZSTFONJEJhYzyUmZGaxSDbdASAnKcaTv34Ts1qtPW7bEliJECKRJAhMrHcQWI/zTCESR1oExpMgMLGe3UE2m7QIRHKSawTGkyAQgLQIhDAzCQIBSPNbJB8ZNTR0JAiEEElNTlKMJ0EghEhK3S0BaREYT4JACCFMToJACCFMToJACJGkYl1CoVAwwXWMfBIEQoik1tnpT3QJI56hg8efffZZPvjgA8LhMH//93/PvHnzWLp0KYqiMGnSJO655x5UVeXpp59m9erVWK1Wli1bRmlpqZFlCSGGgWjX0uh+f2eCKxn5DGsRbNiwga1bt/L73/+eF154gbq6On7+859zyy238NJLL6HrOu+//z4VFRVs3LiRV199lRUrVvCzn/3MqJKEEMOErusE/LGWQGenL8HVjHyGBcHatWuZPHkyN954I9dddx3nnnsuFRUVzJs3D4AFCxawfv16tmzZwllnnYWiKBQWFhKNRmlubjaqLCHEMBAKheLbp3Z2SovAaIZ1DbW0tFBTU8MzzzxDVVUV119/PbquxyeHuN1uOjo68Hq9ZGRkxF/X/XhWVla/752Z6cJqtfT7eXHycnNTE12CEHEtLUe3Tg0E/PL7aTDDgiAjI4OSkhLsdjslJSU4HA7q6urin/f5fKSlpeHxePD5fL0eT009/n96S4ucIQy2xsaORJcgRFxdXWP8diAQoL6+TfbMGAT9BaphP9nTTjuNjz76CF3Xqa+vx+/3c8YZZ7BhwwYA1qxZQ1lZGXPmzGHt2rVomkZNTQ2aph23NSCEGPkCgaMjhXRdJxiUIaRGMqxF8M1vfpNNmzbx7W9/G13XWb58OaNHj+buu+9mxYoVlJSUcMEFF2CxWCgrK2Px4sVomsby5cuNKkkIMUx8+cAfCgVJSUlJUDUjn6HDR3/6058e89iLL754zGNLlixhyZIlRpYihBhGAoHAl+77SU/P6OfZ4uuSTjchRNIJBruCQOm+L11DRpIgEADxoXpCJIPuA7/isPS6L4whQWBiPZf3DYfDCaxEiN66D/yqBMGQkCAwsUgk0uO2BIFIHt1dQ6ozFgRfvmYgBpcEgYn1PPiHw5HjPFOIodU9fFR1xsazxK8ZCENIEJhYNKrFb2uaXCMQycPftc6QmhJrEcgyE8aSIDAxTdP6vC1EonUf+FWXDZAVSI0mQSAA2RdWJJfuFUctbmuv+8IYEgQm1rX+H4Cs4yKSitfrBVVBdcWCoOd6ZGLwyV+/iSk9k0CIJOL1dqDaVVR77BpBR0d7gisa2SQITO1oEEiLQCST9va22GQyq4JiUSQIDCZ//SYmDQKRjEKhEIFAANVhQVEUFLuFtra2RJc1okkQmJiMGhLJqL09dtBXuiaTKU4L7e1tMqDBQBIEJhaJRHvclgllIjl0n/13Ly+hOixEIhEZQmogCQITC4dD8duhUOg4zxRi6Hi9sd3yjgZB7DDV0SG76BlFgsDEei7kFQrJol4iOXQHgWKLHZ6UrpFDXq83YTWNdBIEJtZz/RZZ1Eski/gS1N1BYI19lJMV40gQmFjPg78s6iWSRfcBX1Fjw9oUS+yjLEVtnAFtVfn666/zyCOP0N4eG8ur6zqKorBr1y5DixPGkmsEIjn1Pa5ZJkAaZ0BB8Otf/5oXXniByZMnG12PGEK99yOQUUMiOVgssY6K7uGiuhb7KJMejTOgn2xeXp6EwAjUc1i2jNEWySIlxQWAHo7NbdEjsY8ulythNY10A2oRTJ8+nZtuuokzzzwTh8MRf/xb3/qWYYUJIczJ40kFQA9qvT663Z6E1TTSDSgIvF4vbreb8vLyXo9LEAxv3U3w2G1LAisR4qisrCwAov5Yd6XW9TEzMythNY10AwqCn//850bXIRJAVS09bkv/q0gOOTm5AGi+2FaqUV+Y1NTUXr0RYnAdNwiuvfZann32Wc4777w+r9i///77hhUmjCctApGMXC43Hk8qnb4AuqajdUbIn1CQ6LJGtOMGwf333w/ACy+8MCTFiKGlKEeDQFoEIpmMGlXA3n27iXaEQY/dF8Y5bhCsX7/+uC8uKioa1GLE0Oo5UkhGDYlkkp8/ir17dxOu7+y6L0FgpOMGwYYNG477YrlYPLxpWrTHbVmGWiSP/PxRAITiQTAqkeWMeMcNArlIPLJFo7IMtUhO3ReMI02xpU9yc3MTWc6IN6BRQ3KxeGQKh8N93hYi0bKysmM3unosZeiosQYUBD0vFkciEd577z1Zm2YE6Pl/KP+fIpl0Tyrr774YXAMaKlJUVBT/N3bsWP7lX/6FlStXGl2bMFjP1RxlZUeRTNxud/y205kio9oMNqAWwaZNm+K3dV1nz549cuAYAXqu7y5rvYtkYrUePTTZbAM6TImvYUA/4V/+8pfx24qikJmZycMPP2xYUWJoSItAJKueLYCe812EMU76GoGu6/h8PjyeEy8AdeTIES6//HJ++9vfYrVaWbp0KYqiMGnSJO655x5UVeXpp59m9erVWK1Wli1bRmlp6Vf/bsRJ6XldoOfeBEIkWs9RbNGojGgz2oCidtWqVTz22GP4fD4uvvhizj//fF5//fXjviYcDrN8+XKcTicQG4p6yy238NJLL6HrOu+//z4VFRVs3LiRV199lRUrVvCzn/3s639HYsAikXCP2/LHJpJHz1FsMpDBeANqETz99NM8+OCDvP3225SWlrJ8+XKuueYaLr/88n5f88gjj3DVVVfx3HPPAVBRUcG8efMAWLBgAevWrWP8+PGcddZZKIpCYWEh0WiU5ubm+OqD/cnMdGG1yto4X5fN1nOtIcjNlZEZIjl0djbHb4fDYTIzU3pdNxCDa8A/2SlTpvDUU09x6aWX4na7jzvu/PXXXycrK4uzzz47HgTd21tCbERAR0cHXq+XjIyM+Ou6Hz9RELS0dA60bHEcPt/R6wKBQIjGxo4EViPEUVVVDb3uHzpUR1paeoKqGTn6O9kbUBDk5ORw//33s3PnTh577DEefvhhCgsL+33+a6+9hqIofPzxx+zatYvbb7+d5uajCe/z+UhLS8Pj8eDz+Xo9npoqZ6WJIEsNiWTSvT96z/sSBMYZ0DWCX/ziF8ycOZPnn38el8vFmDFjWLFiRb/P/93vfseLL77ICy+8wNSpU3nkkUdYsGBBfO2iNWvWUFZWxpw5c1i7di2aplFTU4OmaSdsDYjBo6pKj9syMkMkj/b2NgBUj63XfWGMAbUInE4nGRkZbN26la1bt+J2u3nvvfdOatG522+/nbvvvpsVK1ZQUlLCBRdcgMVioaysjMWLF6NpGsuXL//K34g4eT2XDeljBREhEqalJdaDYM10EPKG4/eFMQYUBLfeeis1NTVMmDCh18FjIEHQc+jpiy++eMznlyxZwpIlSwZShhhkvYNAWgQiebS2tgBgzXIQqvRKEBhsQEHwxRdf8M477/S58JwYGWQ/ApFMjhxpAsCWFRt+3tx8JJHljHgDOg2cMGECjY2NRtcihljPPQh67k0gRKI1NTWiOi1YUmPXCBobG07wCvF1DKhFEAgEuPDCC5k8eTJ2uz3++PPPP29YYcJ4gUAgflsm7YhkEQ6HOXKkCUu2A8WqojosNDTWJ7qsEW1AQXDttdcaXYdIAL//6HyMzk6ZmyGSQ0NDPbquY3HHWgOqx8aRpiYikYhMKjPIgH6q3TOCxcjS3t6GolpBsdDWJsPzRHKora0BiHcLWVJtRI4EqK+vo6hodCJLG7GOGwRTpkzp8wJx9yzhXbt2GVaYMF5LSwtYHCiqjdbWll6zv4VIlJqaKgAsqfauj7FAqK6ulCAwyHGD4PPPPx+qOsQQi0QidHS0o6bkgGoj6G3F7+/E5XKf+MVCGKiq6jAAlnR7r49VVZXMm3dGwuoayWTwuEnFWwBWF6o1BehqIQiRYJWVh1FsKmpKbGFJa7qj6/FDiSxrRJMgMKm2tlYAFGsKSlcQdE/iESJRAoEADQ31WDLs8W5K1WFBdVo4LEFgGAkCk+roiC3qpVodKFZH12Oy+qhIrKqqw+i6jjXd3utxS7qdluZmvF75HTWCBIFJdR/0FYsDxRILAvkjE4nW3f1j6eoO6na0e+jwkNdkBhIEJtXZ2bX8t8WOYrH3fkyIBDl8OBYEx7QIMuxdnz841CWZgszOMKnufSAUix1Fif0aeL3eRJYkROxArypY0noHgTXD0fV5uU5gBAkCk+q+RqBYHLFJZUjXkEiscDhMZeVhLGk2FLX3fBbVbUWxqhw4sC9B1Y1s0jVkUt0jhFRrCorV2esxIRLhwIF9RCIRbNnOYz6nKArWLAd1dbWySY0BJAhMqrm5GVQLqDYUxYJidXJElvoVCbRz53YArDnHBkHPxysqdgxZTWYhQWBCuq7T2NiAavPEx2orVjdHmpp6LU0txFDRNI316z9CsarY8119PsdRFJv1vm7dmqEszRQkCEyos9NHIOBHsR1dTkK1u9G0qHQPiYRYv/4jmpuPYC9yo1j7PixZUu1Ysx189tlOdu+W5W8GkwSBCTU3x7b9U61Hz7yUrtuyE5QYas3NR3jppf9GsaqkTM047nNdM7IB+I//eKbXfhri65EgMKHu0UHdM4oB1K4LxjK7WAylqqpKHn74PgKBAK7SLCwu23Gfb8t24pyUTmNjA4899qCsjzVIJAhMqHsTGkXtMVZbjf0B9tysRgij6LrOli0befDB5TQ1NZIyJQPH2NQBvdY1PQtHsYcDB/Zx3/13snfvboOrHflkHoEJxfcn7rH3QPdF42hU9i4WxtF1nc8+28kbb7zG3r27USwKnnl5OEZ7BvweiqrgPi0XS5qdtp3NPPTQvZx66mlceukVjB07zrjiRzAJAhOSzWfEUItEIlRU7OCtt96In8HbRrlwTc86ZjmJgVAUhZTJGVgzHXRWNLN16xa2bt3C7NmncdFFlzBhwiRUVTo8BkqCwIQsltg67+hHh4rqXbdlT1gxWKLRKJ9//hmbNn3Cli2b8PliS5jYCly4pmRizXSc4B1OzJabQto5hYQb/Ph3tVBevoXy8i1kZmUxt+x05s49nZKSCXLycwLyV29CitL/mZKcRYmvIxgMsGfPF3z66WY2b94QX79KdVpwlqThGJs64ADw7YiNYHPPzD7u8xRFwZ7vwpaXQqQxQPBwB621rfz1r2/z17++TXZ2DnPnzmf27NMoKZkoJzt9kJ+ICel6/5PGZEKZOBnhcJj9+/eya1cFu3ZVsH//3vh1JtVhwVGShqPIjTXHedJn5aHq2MKIJwqCboqiYMtLwZaXgh7VCTd0Eqz20VzTzLvvvsW7776F3W5n8uQpTJkyjalTp1NcPO5oC9nEJAhMqPssrXv56Z63u1clFaIvoVCIgwf3s3v35+zaVcHevbsJh8OxTyqxfQSceR7s+a6vdPAfLIpFwV7gxl7gRo9qhOv9hBv8hBv97Ny5Pb6chdOZwpQpU5kyZTqTJ5/C6NHFpmwxmO87FjQ1NQLEt6iEo5PLmpoaElKTSE4tLS3s27ebvXt3s3fvHg4dOtBrZJklzY6zOA1bbgrWHCeqPfnOrhWLir3Qjb0wNpNeC0QINwYIN/oJNfopL/+U8vJPAbDb7ZSUTGTChElMnDiZCRMm4fEMfETTcCVBYEIHD+4HQHVmxh9TnekAHDiwPyE1icTTNI2qqkr27PmCfft2s2fPbo4caTr6BAUsGQ6cWW6s2U5suSmojuQ78J+I6rTiGOPBMSZ2gI92Rgg3+okcCRBpDvD555/x+eefxZ8/qqCQSRMnM3HiZCZNOoX8/FEj7uKzBIHJBAKxX3TVnhafTQygqDZUZxb79u2ho6Od1NS0BFYphkIkEol38+ze/QV79nyO3++Pf16xW7CNcmHLdmLNdmDNcPS7DtBwZnFZsYxNha4JbVooSqQl2BUMQeob66irreGjj1YDkJaWzuTJpzB58tR4d9JwH2QhQWAyW7ZsJBwOY8+ZfMznrGljCDU0s2nTBs47b2ECqhNG0jSNvXt3xxdt27dvz9H+fUB123CM9WDNTsGW7UD12Ebcme9AqHYL9nxXfBVUXdeJtoWIHAkQPhLA2+Rl8+aNbN68EYCUlBQmTTqFSZOmMHNmKWPGjB12PzcJAhPRdZ333nsXULCljz/m87b0cYQad/Dee+9w7rnnD/uzHBE7+O/e/TmbN29gy5ZNtLW1xj9nSbfjyE7DluPElu1ETZHDQV8URcGaEWsROSeko+s6WmeEcFOASFOAYFOA7dvL2b69nNdee5m8vHzKyuZTVjaPsWPHD4tQkP95E9m+vZzDhw9iTR2Daj/2AphqTcGaNpb6+gNs3ryBefPOSECVYjAcPLifNWtWsWXLpqPbktotOMalYi9wYc1Ozgu7X6breqJLOIaiKFjcNixu29HuJH8sGEK1PhrrGnn77Td5++03ycnJpaxsPueccx75+aMSXHn/FN2An3Q4HGbZsmVUV1cTCoW4/vrrmThxIkuXLkVRFCZNmsQ999yDqqo8/fTTrF69GqvVyrJlyygtLT3h+zc2ygqZJ0vTNO69dxlVVYdxjb8Qi7Pv5X61UAe+/W+Tl5vPAw88asqhdMPd6tXv8+KL/4mmaagOC7ZCF/YiN7aclGP2Ak5WkbYQ/rUN5GTn0NzZhuO0zK+0FEUi6FGNUJ2fUI2PcG0nekTD4XRy/XU3UVo6O6G15eb2vbCf5d577713sL/Yn/70J7xeL08++SQLFy7khhtu4PPPP+f666/n5ptvZtWqVUSjUQKBAP/zP//DSy+9xJlnnsntt9/O4sWLT/j+nZ2hwS55xPvwww/46KPVWNPHYc+c2O/zFIsDPRKg48hhUlJcTJx47LUEkZx0Xef3v3+eP/7xVRS7imdeHu7ZOTgK3Vjcw6u/37++iWv/+UfcfPPNZKams/Hd9djHD49hnIqqYE2z4yhy45yYhuq2EqjpYMMn63G53EyY0P/fn9Hc7r5ndRvSCXzhhRdy8803x+9bLBYqKiqYN28eAAsWLGD9+vVs2bKFs846C0VRKCwsJBqNxjdNEYOntbWFP7z2Mopqw5E764TPd+TMRLHYeeONP8TnHIjkV1l5iJUr/wKqQto5hdgL3MOmBdCTFoiQ5Upn4cLYgIWFCxeS5UpHC0QSXNnJUywqznFpeM7IR9d1Xn75haTcUMeQdr/bHZu44fV6uemmm7jlllt45JFH4mckbrebjo4OvF4vGRkZvV7X0dFBVlbWcd8/M9OF1Zr8/ZvJQNM0fvnLR+n0+XDkn4ZqSznhaxSrA0feqQRqN/Cf//kMP//5z2Ua/jCQlTWNsrIyNm/ejH9PK+7SbBTL8Lvgr0d1mpqaeO+991i4cCHvvfceTU1NuKL5iS7tK9HCGoE9bQBccskljBmTm+CKjmVYB3BtbS033ngjV199NYsWLeKxxx6Lf87n85GWlobH4+m1pIHP5yM19cSbU7S0yOYpAxGNRvntb5+lvLwci7sA23G6hL7Mmj4Oq7eGXbt2cf/9D/GjH92IzXb83aNE4n3/+9dRW3sv1QeqCFV34ij24BiXijVtePSvdwuFQjzzzDP84Q9/oKmpiVAoRN9b2icnXdeJtAQJHmgnVOVDj+rMmDGLSy+9MqHXOPu7RmDI6UJTUxM/+MEPuO222/j2t78NwLRp09iwYQMAa9asoaysjDlz5rB27Vo0TaOmpgZN007YGhAD09TUyFNPreDjj9eipmSTUnTGSfURK4qCs2AeFlceW7Zs5IknHqWhod7AisVgSElxcdttd3LRRYtwO1wE9rbRtrKKtg9rCBzqQAsOn42HQqEQNTU1hELD55pgtDOCf18bbR9U0766huAhL9mZOVxxxWJuvPHmpG1ZGzJq6IEHHuCdd96hpKQk/tidd97JAw88QDgcpqSkhAceeACLxcJTTz3FmjVr0DSNO+64g7KyshO+v4wa6l97ext//vMbrFq1kmg0gsWVT8qYs1DUvs/mA/XlADjz+x7NoGsR/NXriXprUFWVc845j0WL/o6MjMw+ny+SRyQSYevWzXz44Qd89tnO2IMKWDMd2Ea5sI9yYUm3J91F5KgvTOtfKo95POOCMbEhm0lE13UizUHCdZ2E6jqJtsVCS1VV5swp45xzzmfq1OlJMyenvxaBIUFgNAmC3lpbW9i+vZxt27ayc+d2wuEQqs2NPXcm1rTi4+4/4N37JgCeiZf2+xxd14l0VBJq3IEW6sBqtTJ9+kxmzZpDaelssrIGtkywSJyGhno2bfqEbdu2sm/fnvj4fDXFii0/Bfuo2Hr+ybCERLIHgRaMEm7wE6rrJFzvRw/FWlkWq5Upp0yltPRU5s07g/T09ARXeiwJghEkGAxQWXmYioodbNu2Nb6IHIBqT8WWOQlb5gQU5cTN0IEEQTdd1wi3HiDc/AVaqD3++JgxY5k161RmzCiluHgcTqfzOO8iEs3r7WDnzu1s376VHTu2Hb1OpyrYsp3YRqVgy3dhSU3MkFMtEKHl7cPHPJ55cTGqc+jntei6TrQlSKjeT7i+k0hLELqOmhkZmcyadSqlpacybdp0HI7k/t2XIBiGdF2ntbWVysqDVFYe5vDhQ1RWHqK+vu7ojEtFwZKSh9VTiNVTgOo4ucXiTiYIetJCXiLeGiLeGqKdDfFtLxVFITc3j+LisYwZE/tXXDyWzMyspOuCELFRZfv27WHHjm3xmefdVFd3a8Eday1Yhu7/r+WvlWjeHusgeWxk/p8xQ/b19bBGqD7W3ROp98evraiqysSJk5k5cxYzZ85mzJjiYfV7LUGQxDRN48iRJhoa6mloqKe+vo6qqtiB3+vt/b0qFjuqIx3VkYnFlYPVParXBjMn66sGQU96NEzEV0/U34AWaEULtqJHe1/gc7vdFBePY/ToYvLzR5GXl09eXj7Z2TlJewHNjNraWtmxYxs7dmxjZ8V2/J2xEXqKTcVe4MJe5MGWb/wM5UhbiLYPqkCPhUDq/HzDZxbrYY1QXSeham+syycaOzSmp2d0HfhnMX36TFwut6F1GEmCIMHC4TBNTY1dB/s6Ghoa4h+bmhp6bfbRTbG5sTgzUR0ZsY/ODBSra1DPQAYjCL5M13X0SCdaoJVosDUWDoEWtLD3mOeqqoWcnJx4MOTljSIvL4+8vFHk5uZisw2vYY8jSTQaZd++PXz66WY2bf6Elq7JnvFQGOOJtRQMOiNuefcwuq6TddFYQ94fQNd0QjU+QlW9D/6FhUWUlc3n1FPLKC4efquJ9keCwGC6rtPe3kaAkhjfAAAUh0lEQVRjYwONjQ00NTXS2NhIU1PsfnPzkT4X0FIsDhS7B9XmQbV7UO2psduOdBSL8RfGjAiC/ujRMFqoHS3UgRbyooW9aKEO9JAPPXrsbEtFUcjMzCI3N4+cnFxyc/Pit3Ny8khPT0+a0RgjnaZpHDiwj02bNvQKBUuqDefEdBzFnkGfvNbybuw6QeaFxYP6vhDbcyB4oIPA/nY0f2zGcvfBf+7c0ykqGj3oXzMZSBAMgmAwSH19XdeB/ujBvrGxnqamJsLhvsc7K9aU2EHe5okd9LsP9nbP1+rWGQxDGQTHo0fDXcHQHQ7e+H090vcEQpvN1hUKsWDIzc3tCoo88vNHyUVrg2iaxv79e1m1aiUbNqyPLW5nt+AYn4pzUvqgrWpqRBBEOyP4d7cSOtSBHtVxOBycffa5nHPO+SP24N+TBMFJCAaD1NZWU11dRU1NNTU1VVRXV3HkSFM/Z/V2FJsb1eZGsXlQbW5Uuzt24Le5UdTk7QP37n0TXddJnXRZokvpl65F0cM+tK5/etiLFvKhhb3oYd8x1yO6ZWfnUFQ0msLC0RQWFlFUNJqCgiIJiEHU0tLCBx/8ldWrV+Lz+VAdFlyl2dhHu792d8pgBoGu6QT2teHf1Yoe0cjKyuZv/uZCFiw4d1j3+Z8sCYJ+aJrGzp3b+OKLz497wFcsTlRHWmyLR3vsAB87y3cn/Kz+q4oGWolUryInJ5sj7X4sufP7XZ46menRUCwkQl0hEfahBdvRQm3okWO7nHoGxKRJk5k1a450MX1NwWCQlSvf5Y03XycSDmPLS8E9JxeL66sP9xysIIi0BvF+2ki0NYTb7eHKK6/mG98425SDFCQIvsTv97N27YesXPkujY0N8cfjB3xH+tGP9nRUa9/Ltw5nocq/cO0Prokv7PXcb1/ANuaCRJc1qPRokGiwHS3Y1vXv2IDIzs7h/PMvMN3ZoREaGup5/vn/4LPPdqI6LKR+YxTWzK/2tzMYQRCq9eHd2IAe1TnzzAVceeXVpt6PW4Kghw8//IBXXvkdgYAfFBVb2jis6WNRHRkj8oDfFy3iJ923iWeffTb+2LXXXkubey6q9cQrlA53sYBoI9J2mEj7QXQtgt3u4IorrmThwosSXd6wpus6K1f+hZdffgEsCp55edhHnfyScV83CAL72/Fta8Jus3PttT/m1FNPvHzNSDeki84lu3379sRCALC4R2HPmYrVnW+aEABAi8aX+gXiS/2iDZ9Fyb4OxeLA6srDnj0Fi7sAgFAoyJ49XyS4suFPURQWLryQG264BYtiwftJPeFG/0m/j73Ijb3oq7XQAoc68JU34fGk8tOf3iUhcAKmbBFomsbmzRt4880/UlNTBYBiT+0as5+JxZmB6sxEtY7ci4payItv35+x2+3k5OTEl/p1T7ikz/2MRwI9GiQaaEELtHR9bI0vlZGfP4pFi/6O+fO/Ycq+Y6NUVOzgiSceRVN10hYUYE03/mQrVNdJx8d1uFJcLFv2MwoLiwz/msOFdA31QdM0Pv10M6tWvcfBgwfw+3sPU1SsKajOzKMB4UhDsXuOu4jbcNEdBF82EoJA1zX0sI9osC0+mS0abEEP9/7/dTqdjB07nnPOOZ95806XC8YG+eSTdTz33K9QXVbSzy1CdRoXtJG2EO0f1mBRLPz0tjtlq9Uv6S8ITL0zuaqqlJXNo6xsHrqu09TUyOHDBzl06CCHDx/i8OGDtLbWEPXWHH2RonZN+OoaQRS/oJyKopr6xznkdC0Sm5wWbI9NVOv+GOqIr33ULS0tneJTZjF27FiKi8dRXDyO3Nw8OfgPgdNPP5PGxgb++MdX6dhQT9rZBYYsUaGFonR8Uo8e0fiX634sIXAS5MjVpXuxtNzcPE47bV788ba2NiorY8FQW1tDTU01tbXVBDqqjn0Pm7srHNJj3UuODFRH2ohoQSSSrmuxA36gFS3YEh8FpId9xzzX4XBSMHYcBQWFFBYWMWZMMcXF42T/hAS75JJvUVl5iM2bN+LbfgTP7JxBfX9d0/FubEDzhbnkkm8xb97pg/r+I50EwQmkp6eTnj6LGTOObvoeWxW0pSsUaqitrY6HRHt7LVFfLfF1ExU1FgyOrusOzgwsjoxhO/fAaHo0fHR9omAL0UArWrAN9N4XsVNTUykYP4XCwiIKCgopKCiisLBIVjlNUoqi8M//fB11dXVU7T+MNd2Oc/zgDePsrGgm3OBn1qxT+da3vj1o72sWpr5GYASv10tNTVV8yejDhw9RXV1JJBLp9TzF5sHqzsfiLsDqzhvyYEiWawR6NEy0s4GIr46ory7WrdODxWKlqGh015l9rFunqGg0Hs+J97YWyaehoZ777rsTf8BP6oICbFlff0BGsMqLd2MD+aMKuPuu+3G5htPuxkNLLhYnUDQapa6ulsOHY/sKVFYeYv/+fT0uTitYUrKxuEfF9hRwGn9Wq0X8+Pa8cczj7kmXGTqPQNd1tEALEV8tUV8dUX8TdP0KOp1Oxo+fEN/DoLh4LKNGFWK1SsN1JKmo2MGKFQ+jOC2kf7Pwa202E2kL0r66FrvNzt133S8jhE5AgiDJRKNRDhzYx86d26mo2MH+/XuPbh/ozMKRMx2Lp9DQQPDuewu9xxm4ak/FPeFvDflauq4T9dURaqqIHfyJdReMGzee6dNLmTGjlJKSiXLQN4l33vlfXn3191hznKSd9dUuHmthjfYPqon6wvz4xz9hzpy5BlQ6skgQJDmfz8uuXZ+xYcM6tmzZBIDqyMSRPwure5QhXzMaaKXzwF8AHdWeirPoTEPWGop0NhCs34YWOALA7NlzOP30M5k2bYZ08ZiUruv86ldP8Omnm0g5JQPX9KyTfr13QwOhGh8XX3wp3/72VQZVOrJIEAwjVVWV/PnPf2LTpk/QdXCMKsOeOcGQr2X06qPhtoMEajeArnPaaXO55JK/Y+zYcYZ8LTG8dHb6+NnP7qSxsYG0swuw5Q68SzJwoB3f1iYmT57CbbfdKZMAB0iCYBjat28PTz75OF5vB/a8WTiypw761zByP4JQ8x6C9VtISXFx0023csopg1+/GN7279/LQw/dCw6V9POLBrSXQdQbpu2Dapx2J/ff9whZWdnGFzpCyFpDw9CECZNYtuxeMjOzCTVsI9y6P9ElDVi4/TDB+i2kpaVzxx3LJQREn0pKJnLJJd9C80forGg54fN1Xce7tRE9onHNP/5AQmCQSBAkuVGjCrj11qW4XG4CdZsItx1MdEknFG6vIlCzAYfDwb/+6+2MHj34Ww2KkeOSS75FQUEhwQPtRFqCx31uqNpHpDFAaempzJ9/xhBVOPJJEAwDhYVF3HLLbaQ4nQRqPiHYtKvPndISTdd1Qs27CVSvxW6zsmTJrRQXj0t0WSLJWa1W/vEfvw+Ab+eRfp+nazqdO5uxWq1cffU/ycTBQSRBMExMnDiZO+64l8zMLEKN2/BXrkYLeRNdVpwW7sRf9RHB+k9JTUtn6dK7mTZtRqLLEsPE1KnTmTFjFpHGQL9LVgcPdaB1Rjj33L8hLy9/iCsc2SQIhpHRo8dw1133U1o6m6ivns4D7xI68jl6AvcQ0HWNUPNuOve/Q9Rbw5Qp07n7rvsYN64kYTWJ4emyyy4HwL+79ZjP6bpOYE8bVquViy9eNNSljXgye2eYyczM5Oabb+Pjj9fy0u+fp7OhnHDLHuy5M7GmjT3p5rI19av13+u6TqSjklDjdrSQF6czhcWLv8uCBd+UJrv4SiZMmERJyQT2799HtDOMxWWLfy7SGCDqDfONb5wtCwgaQIJgGFIUhW9842xKS2fz5z//iffff49AzSeoRz7HkTvzpGYkO/Nnn9TXjs0QrifYuB0t0Iyqqpx33kIWLbqc9PT0r/LtCBF3zjnns3//PoKHvLimHj3gBw7Fhoyfe+75iSptRJN5BCNAU1Mjf/zjq3zyyTp0XUdNycaRO3PQZyRHOhsINe4g2tkIQFnZfK644kry8wsG9esI8+rs7OTmm68Fj4WM80cDoEd1Wt4+RFZaFo8++qS0OL8G2ZhmBMvJyeWHP7yBiy5axBtv/IEtWzbhP7wai7sAR96sr71shBZsJ9iwjYi3GqBrqd/vyAxhMehcLhfTp89k+/byePdQuMmPHtaYM2euhIBBJAhGkNGjx3DjjT/h4MH9vPrq79m1q4LOA3XYMsbjyJ2FYj25/WL1aIhg4w7CLXsBnUmTTuE73/l72flJGGr69FK2by8n3ODHMs4WH0U0c+asE7xSfFUSBCPQuHEl/N//u4wdO8p55ZXfUVu7n4i3BueouVhTB7ZMb8RbS7BuE1q4k7y8fL7znauZM6dMzsiE4bqHHYcbAzjHpRFpDGCxWJg06ZQEVzZySRCMUIqiUFp6KtOnl/KXv7zFH//4B/xVH2HLKMEx6jQUpe81XXRdI1i/lXDLHlRV5bLLruBv//YyWR5aDJmCgkJSXC6CzUH0qEakLcT4sSU4HCfXohUDlxR/3Zqmce+99/LFF19gt9t54IEHGDt2bKLLGhEsFgsXX3wps2bN4d//3685fGg/WthHStFZKBZbr+fqWgR/9Xqi3hoKC0fzox/dIDODxZBTVZWS8ROoqNhBuDEAmk5JycRElzWiJcWEspUrVxIKhXjllVe49dZbefjhhxNd0ohTVDSaO5bew+zZc4j66vFXfojeYx9gXdfwV31E1FvDtGkzuPPOeyUERMJ0/+4FK71d9+XE0EhJ0SLYsmULZ599NgCzZ89m586dx31+ZqYLq1XWHz95qdx773Ief/xx1q5dS7C+HOeo0wBiw0J99ZSVlbFs2TJsNtsJ3ksI40ydOol33oFQVSwIZsw4pd+hj+LrS4og8Hq9eDxHN0y3WCxEIpF++6VbWjr7fFwMzD/8ww84cOAg1dV7sKWNBdVK6Mgu8vLy+d73rqW1NQAEEl2mMDGXq2vIc9csJ4cjXeYPDYKk3o/A4/Hg8/ni9zVNk4uTBnI4nPHVHoNNFYSaKgC4+urv4nK5E1maEADk5x+dDOnxpOJyuRJYzciXFEEwZ84c1qxZA0B5eTmTJ8s4daOdcspUJk6cTNRXS6SjkjFjimWctkgaLpcbe9cooezsnARXM/IlxWn3woULWbduHVdddRW6rvPQQw8luiRTmDOnjL17dwNw6qkyR0AkD0VRcDochIJBMjNlkTmjJUUQqKrKfffdl+gyTKfnDGGZrCOSlccjF4mNlhRdQyIxCgoK+7wtRHKItVBVVQ5TRkuKFoFIDLfbw403/oRoNCKbgIukJV2WxpMgMLnTTpub6BKEOK5huFL+sCNtLiFEUupuCUjXkPHkJyyESEpnnrkAkIEMQ0F2KBNCJKVwOMzhw4cYP75EWgWDpL+ZxRIEQghhEkm9xIQQQojEkSAQQgiTkyAQQgiTkyAQQgiTkyAQQgiTkyAQQgiTkyAQQgiTG5bzCIQQQgweaREIIYTJSRAIIYTJSRAIIYTJSRAIIYTJSRAIIYTJSRAIIYTJSRAIIYTJSRCYlKZpLF++nMWLF3PNNddw6NChRJckRC/btm3jmmuuSXQZpiCb15vUypUrCYVCvPLKK5SXl/Pwww/zm9/8JtFlCQHAv//7v/Pmm2+SkpKS6FJMQVoEJrVlyxbOPvtsAGbPns3OnTsTXJEQRxUXF/PUU08lugzTkCAwKa/Xi8fjid+3WCxEIpEEViTEURdccAFWq3RYDBUJApPyeDz4fL74fU3T5A9PCJOSIDCpOXPmsGbNGgDKy8uZPHlygisSQiSKnAKa1MKFC1m3bh1XXXUVuq7z0EMPJbokIUSCyDLUQghhctI1JIQQJidBIIQQJidBIIQQJidBIIQQJidBIIQQJifDR4Vp+Xw+Hn/8cdauXUtKSgoej4clS5Zwxhln9PuaVatWcfDgQb7//e8PYaVCGEuCQJiSrutcd911TJ06lbfeegu73c5nn33Gj370I37xi18wf/78Pl8nazKJkUi6hoQpbdy4kZqaGu644w7sdjsA06ZN4/rrr+fXv/4111xzDRs2bACgqqqK8847j7179/Lyyy/z8ssv89prr9Ha2sqNN97IRRddxGWXXcbHH38MxFoNl112GYsWLeKGG26gqakJgPPOO49f/OIXXH755Vx55ZWsXr2af/qnf+Kcc87h7bffBqCpqYkbbriByy+/nCuuuIL169cn4KcjzEaCQJjSjh07mDFjBoqi9Hp87ty57Nixo8/XTJw4kauuuoqrrrqKK664gieffJLi4mLeeecdHn30UZ544gmOHDnC8uXL+dWvfsX//u//MmfOHO677774e+Tk5PD6668zYcIEnnvuOX7729/y2GOP8dxzzwHw4IMPcsUVV/D666/zm9/8huXLl+P1eo37QQiBdA0Jk1IUhWg0eszj4XD4mHDoz6ZNm3j88ccBOOWUU3jllVdYtWoVpaWljB49GoDFixfHD/IACxYsAKCwsJC8vDysViuFhYW0t7cDsH79evbv388vf/lLACKRCJWVlUydOvWrf7NCnIAEgTClWbNm8cILLxAOh7HZbPHHy8vLmTFjBpqm0b36Sn/Lc1ut1l6hsW/fPjRN6/UcXdd7vb7n1+prtVdN0/jv//5vMjIyAGhoaCA7O/srfIdCDJx0DQlTKisrY+LEiTz00EOEw2EgdiH4N7/5DTfccAOZmZns3bsXiO3m1q3nvg1lZWW89dZbQCwEfvjDHzJr1iy2bdtGVVUVAK+88kq/F577cvrpp/PSSy8BsHfvXhYtWoTf7//637AQxyEtAmFaTz/9NP/2b//GJZdcgsViIT09nccee4z58+eTkpLC0qVLee211zj//PPjr5k7dy633347OTk53HTTTdx1111ceumlWK1WHn30UXJycrjvvvv48Y9/TDgcprCwkAcffHDANd11110sX76cRYsWAfDoo4/22kBICCPI6qNCCGFy0jUkhBAmJ0EghBAmJ0EghBAmJ0EghBAmJ0EghBAmJ0EghBAmJ0EghBAm9/8BDf/rT0xpsRQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xff82c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10024438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x101110f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x102241d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for name in trainFilled.columns:\n",
    "    if name != 'Outcome':\n",
    "        fig=plt.figure()\n",
    "        sns.violinplot(x='Outcome', y=name, data=trainFilled)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "通过violin 图我们可以发现 怀孕次数多可能导致糖药病的几率大一些，Glucose 不是糖药病的比是糖药病的人的均值和分布情况都低很多。skinThickness Insulin BMI是糖药病的人都比不是糖药病的普遍要高一些。 年轻人得糖药病的几率要小一些。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pregnancies</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>BloodPressure</th>\n",
       "      <th>SkinThickness</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>DiabetesPedigreeFunction</th>\n",
       "      <th>Age</th>\n",
       "      <th>Outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.00000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.845052</td>\n",
       "      <td>121.694010</td>\n",
       "      <td>72.399740</td>\n",
       "      <td>29.204427</td>\n",
       "      <td>156.763021</td>\n",
       "      <td>32.44642</td>\n",
       "      <td>0.471876</td>\n",
       "      <td>33.240885</td>\n",
       "      <td>0.348958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.369578</td>\n",
       "      <td>30.462388</td>\n",
       "      <td>12.108068</td>\n",
       "      <td>8.933982</td>\n",
       "      <td>88.802675</td>\n",
       "      <td>6.87897</td>\n",
       "      <td>0.331329</td>\n",
       "      <td>11.760232</td>\n",
       "      <td>0.476951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>44.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>18.20000</td>\n",
       "      <td>0.078000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>99.750000</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>121.500000</td>\n",
       "      <td>27.50000</td>\n",
       "      <td>0.243750</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>32.05000</td>\n",
       "      <td>0.372500</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>206.000000</td>\n",
       "      <td>36.60000</td>\n",
       "      <td>0.626250</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>17.000000</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>122.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>846.000000</td>\n",
       "      <td>67.10000</td>\n",
       "      <td>2.420000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Pregnancies     Glucose  BloodPressure  SkinThickness     Insulin  \\\n",
       "count   768.000000  768.000000     768.000000     768.000000  768.000000   \n",
       "mean      3.845052  121.694010      72.399740      29.204427  156.763021   \n",
       "std       3.369578   30.462388      12.108068       8.933982   88.802675   \n",
       "min       0.000000   44.000000      24.000000       7.000000   14.000000   \n",
       "25%       1.000000   99.750000      64.000000      25.000000  121.500000   \n",
       "50%       3.000000  117.000000      72.000000      28.000000  130.000000   \n",
       "75%       6.000000  141.000000      80.000000      33.000000  206.000000   \n",
       "max      17.000000  199.000000     122.000000      99.000000  846.000000   \n",
       "\n",
       "             BMI  DiabetesPedigreeFunction         Age     Outcome  \n",
       "count  768.00000                768.000000  768.000000  768.000000  \n",
       "mean    32.44642                  0.471876   33.240885    0.348958  \n",
       "std      6.87897                  0.331329   11.760232    0.476951  \n",
       "min     18.20000                  0.078000   21.000000    0.000000  \n",
       "25%     27.50000                  0.243750   24.000000    0.000000  \n",
       "50%     32.05000                  0.372500   29.000000    0.000000  \n",
       "75%     36.60000                  0.626250   41.000000    1.000000  \n",
       "max     67.10000                  2.420000   81.000000    1.000000  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trainFilled.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "通过填补缺失值，极大地减小了 SkinThickness 和  Insulin 的方差，但是 Insulin的方差仍很高。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  5.4 关联性分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x102d73c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cols=trainFilled.columns\n",
    "data_corr=trainFilled.corr().abs()\n",
    "plt.figure(figsize=(15,12))\n",
    "sns.heatmap(data_corr,annot=True)\n",
    "sns.heatmap(data_corr,mask=data_corr<1,cbar=False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Glucose与Insulin和是否是糖药病相关性高一些。年龄与怀孕次数相关性较高，BMI 与SkinThickness 相关性较高。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 6. 数据预处理"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.1 分离目标值和特征值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pregnancies                 0\n",
       "Glucose                     0\n",
       "BloodPressure               0\n",
       "SkinThickness               0\n",
       "Insulin                     0\n",
       "BMI                         0\n",
       "DiabetesPedigreeFunction    0\n",
       "Age                         0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Y_train = trainFilled['Outcome']\n",
    "X_train = trainFilled.drop([\"Outcome\"], axis=1)\n",
    "\n",
    "X_train.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.2 标准化数值并且分离测试值和训练值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda\\lib\\site-packages\\sklearn\\cross_validation.py:41: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.\n",
      "  \"This module will be removed in 0.20.\", DeprecationWarning)\n"
     ]
    }
   ],
   "source": [
    "# 数据标准化\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "# 采用sklearn的分割函数\n",
    "from sklearn.cross_validation import train_test_split\n",
    "\n",
    "# 初始化特征的标准化器\n",
    "ss_X = StandardScaler()\n",
    "\n",
    "# 分别对训练和测试数据的特征进行标准化处理\n",
    "X_train = ss_X.fit_transform(X_train)\n",
    "\n",
    "# 分割比率20%\n",
    "x_train, x_test, y_train, y_test = train_test_split(X_train, Y_train, test_size=0.20, random_state=20) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 7. Logistic 模型训练及评估"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 7.1 通过gridSearchCV 寻找最佳参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "#需要调优的参数\n",
    "# 请尝试将L1正则和L2正则分开，并配合合适的优化求解算法（slover）\n",
    "tuned_parameters={'penalty':['l1','l2'],'C':[0.01,0.03,0.05,0.07,0.1,0.3,0.5,0.7,1,3,5,7,10,20,50,70,100], 'solver':['liblinear'],'multi_class':['ovr']}  \n",
    "\n",
    "lr_penalty= LogisticRegression(tol=1e-6,class_weight=\"balanced\",random_state = 20)\n",
    "grid= GridSearchCV(lr_penalty, tuned_parameters,cv=5, scoring='neg_log_loss')\n",
    "grid.fit(x_train,y_train.ravel())\n",
    "\n",
    "# 获得预测值\n",
    "lr_predict_test =grid.predict(x_test)\n",
    "lr_predict_train = grid.predict(x_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于数据集比较小，我才用了GridSearchCV进行调参， 由于是不是糖药病的样本不均衡，我才用class_weight = 'balanced'选项。 评分选择了 neg logloss，采用一般的五则交叉验证进行训练模型。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 7.2 查看训练出的评分和准确率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9\n",
      "{'penalty': 'l2', 'multi_class': 'ovr', 'C': 0.1, 'solver': 'liblinear'}\n",
      "LogisticRegression(C=0.1, class_weight='balanced', dual=False,\n",
      "          fit_intercept=True, intercept_scaling=1, max_iter=100,\n",
      "          multi_class='ovr', n_jobs=1, penalty='l2', random_state=20,\n",
      "          solver='liblinear', tol=1e-06, verbose=0, warm_start=False)\n",
      "0.46462674021183537\n"
     ]
    }
   ],
   "source": [
    "print grid.best_index_\n",
    "print grid.best_params_\n",
    "print grid.best_estimator_ \n",
    "print -grid.best_score_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('best params for logistic regression: ', {'penalty': 'l2', 'multi_class': 'ovr', 'C': 0.1, 'solver': 'liblinear'})\n",
      "('best neg lose for logistic regression: ', 0.46462674021183537)\n",
      "confusion matrix:\n",
      "[[43 17]\n",
      " [18 76]]\n",
      "regression report:\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          1    0.70492   0.71667   0.71074        60\n",
      "          0    0.81720   0.80851   0.81283        94\n",
      "\n",
      "avg / total    0.77346   0.77273   0.77306       154\n",
      "\n",
      "accuracy score for train data: 0.82736\n",
      "accuracy score for test data: 0.77273\n"
     ]
    }
   ],
   "source": [
    "print(\"best params for logistic regression: \",grid.best_params_)\n",
    "print(\"best neg lose for logistic regression: \",-grid.best_score_)\n",
    "print(\"confusion matrix:\")\n",
    "print(metrics.confusion_matrix(y_test, lr_predict_test, labels=[1, 0]) )\n",
    "print(\"regression report:\")\n",
    "print(metrics.classification_report(y_test, lr_predict_test, labels=[1,0], digits=5))\n",
    "print(\"accuracy score for train data: {0:.5f}\".format(metrics.accuracy_score(y_train, lr_predict_train)))\n",
    "print(\"accuracy score for test data: {0:.5f}\".format(metrics.accuracy_score(y_test, lr_predict_test)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "找到最优解C值为0.1，正则项为 L2,准确率在训练集上面的0.82 在测试集上面的准确率为 0.77, nll -0.464"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda\\lib\\site-packages\\sklearn\\utils\\deprecation.py:122: FutureWarning: You are accessing a training score ('mean_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n",
      "C:\\Anaconda\\lib\\site-packages\\sklearn\\utils\\deprecation.py:122: FutureWarning: You are accessing a training score ('std_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,u'neg-logloss')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xfcafd68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot CV误差曲线\n",
    "test_means = grid.cv_results_[ 'mean_test_score' ]\n",
    "test_stds = grid.cv_results_[ 'std_test_score' ]\n",
    "train_means = grid.cv_results_[ 'mean_train_score' ]\n",
    "train_stds = grid.cv_results_[ 'std_train_score' ]\n",
    "\n",
    "\n",
    "# plot results\n",
    "n_Cs = len(tuned_parameters['C'])\n",
    "number_penaltys = len(tuned_parameters['penalty'])\n",
    "test_scores = np.array(test_means).reshape(n_Cs,number_penaltys)\n",
    "train_scores = np.array(train_means).reshape(n_Cs,number_penaltys)\n",
    "test_stds = np.array(test_stds).reshape(n_Cs,number_penaltys)\n",
    "train_stds = np.array(train_stds).reshape(n_Cs,number_penaltys)\n",
    "x_axis = np.log10(tuned_parameters['C'])\n",
    "\n",
    "for i, value in enumerate(tuned_parameters['penalty']):\n",
    "    plt.errorbar(x_axis, -test_scores[:,i] ,label = tuned_parameters['penalty'][i] +' Test')\n",
    "    plt.errorbar(x_axis, -train_scores[:,i],label = tuned_parameters['penalty'][i] +' Train')\n",
    "\n",
    "plt.legend()\n",
    "plt.xlabel( 'log(C)' )                                                                                                      \n",
    "plt.ylabel( 'neg-logloss' )\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xcc6a2b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x_axis, -test_scores[:,1], 'b-')\n",
    "plt.xlabel( 'log(C)' )                                                                                                      \n",
    "plt.ylabel( 'neg-logloss' )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "根据C的取值 测试集的变化可以看出在 log(c) = -1 左右取值最小"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 8. 线性SVM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 8.1 模型训练及最优值寻找"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 载入库包\n",
    "from sklearn.svm import LinearSVC\n",
    "\n",
    "tuned_parameters_svc= {'penalty':['l2'],'C':[0.001,0.01,0.05,0.1,0.5,1,1.5,5,10,50,100,200,500,1000,5000,10000],'loss':['hinge']}\n",
    "grid_svc=GridSearchCV(LinearSVC(tol=1e-7,class_weight=\"balanced\", random_state=42),tuned_parameters_svc) \n",
    "grid_svc.fit(x_train,y_train)\n",
    "svc_predict_test =grid_svc.predict(x_test)\n",
    "svc_predict_train =grid_svc.predict(x_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 8.2 结果评分及曲线图绘制"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('best params for Linear SVC: ', {'penalty': 'l2', 'loss': 'hinge', 'C': 100})\n",
      "('best score for Linear SVC: ', 0.8485342019543974)\n",
      "confusion matrix:\n",
      "[[46 14]\n",
      " [12 82]]\n",
      "regression report:\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          1    0.79310   0.76667   0.77966        60\n",
      "          0    0.85417   0.87234   0.86316        94\n",
      "\n",
      "avg / total    0.83038   0.83117   0.83063       154\n",
      "\n",
      "accuracy score for train data: 0.85668\n",
      "accuracy score for test data: 0.83117\n"
     ]
    }
   ],
   "source": [
    "print(\"best params for Linear SVC: \",grid_svc.best_params_)\n",
    "print(\"best score for Linear SVC: \",grid_svc.best_score_)\n",
    "print(\"confusion matrix:\")\n",
    "print(metrics.confusion_matrix(y_test, svc_predict_test, labels=[1, 0]) )\n",
    "print(\"regression report:\")\n",
    "print(metrics.classification_report(y_test, svc_predict_test, labels=[1,0], digits=5))\n",
    "print(\"accuracy score for train data: {0:.5f}\".format(metrics.accuracy_score(y_train, svc_predict_train)))\n",
    "print(\"accuracy score for test data: {0:.5f}\".format(metrics.accuracy_score(y_test, svc_predict_test)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "通过 GridSearchCV进行网格寻找，损失函数采用hinge-loss,采用不同的C值，最后发现 C=100时 为最优解。最好评分 0.848,在测试上的准确率为0.85。在训练集上的准确率为 0.83"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,u'accuracy')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAEJCAYAAAB7UTvrAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzs3Xl8VPW9//HXLJksM5N9spMAWdgRg1svBReMUnBBVEAU9SdWXKrtLbVWq5aiBuwtva0IXrWKNW4gLohLRRShggtSI0YgQAgJWUhCtlkyyWzn90dgICUJIclkMsnn+XjwgJlzzpx3BpjPnPPdVIqiKAghhBCA2t8BhBBC9B9SFIQQQnhJURBCCOElRUEIIYSXFAUhhBBeUhSEEEJ4aX31wh6Ph8WLF1NYWIhOp+Pxxx8nLS3Nu/2FF17ggw8+QKVSceedd5KTk4Pb7Wbp0qUUFBTgcDi49957ufjii30VUQghxH/wWVHYtGkTDoeDNWvWkJ+fz7Jly3jmmWcAMJvN5OXlsXHjRux2OzNnziQnJ4f169fjcrl44403qKqq4qOPPvJVPCGEEO3wWVHYuXMnkydPBmDChAkUFBR4t4WGhpKUlITdbsdut6NSqQD44osvyMrK4o477kBRFB555BFfxRNCCNEOnxUFq9WKwWDwPtZoNLhcLrTa1lMmJiYyY8YM3G43CxcuBKC+vp6SkhKeffZZduzYwYMPPsirr77a6XlqaizdzhgVFUZ9fVO3j+9LgZQVAitvIGWFwMobSFkhsPL2NKvJZGz3eZ8VBYPBgM1m8z72eDzegrB161aqq6v59NNPAViwYAHZ2dlERkZy0UUXoVKpOO+88zh06NBpzxMVFYZWq+l2zo7emP4okLJCYOUNpKwQWHkDKSsEVl5fZPVZUcjOzmbz5s1Mnz6d/Px8srKyvNsiIiIICQlBp9OhUqkwGo2YzWYmTpzIli1buPzyy9m7dy+JiYmnPU9PK2VPrjT6UiBlhcDKG0hZIbDyBlJWCKy8Pc3a51cKOTk5bNu2jblz56IoCrm5uaxevZrU1FSmTp3K9u3bmT17Nmq1muzsbCZNmsR5553HH/7wB2bPno2iKPzxj3/0VTwhhBDtUAX6LKk9rZSD5VtBXwukvIGUFQIrbyBlhcDK66srBRm8JoQQwkuKghBCCC8pCkIIIbykKAghhPDyWe8jIcTgpSgKBbV7qK+u5aemSahVg+P754cfbqCk5BB33XUva9a8yqZNGwH4yU8mcdttd3j3q6+v55FHHgDgwIF9DBmSSnBwCNOmTeeKK2Z2+XybN29i/PgJxMTE9trPIEVBCNGryiwVvHXgffbVHwAgfkIiI6Iz/Jyqb5WXl7Fx4z957rmXUKlU3HPP7UyZcjEZGZkAREVF8fTTzwHwi1/cwf33P0Ra2tAzPs/ata+TmTmiN6NLURBC9I7GFgvvH/yYLyt3oKAQFxpLtf0oZdaKQVcU4uMTWL58BRpN62wLLpcLnU7XpWOPHKnkT3/KxeFoISQkhAceeJjw8HAeeeR3NDU10dLSwj33/BK12sXBgwf44x8f5v/+70XvuXpKioIIeIqi0NDSSIn5MA0OM/GhJhL0cUQGR3gnW/Q3RVGwu5qxOCyYvb+suBX3Gb9WkjWWYJceU1gMxiCD339Gh9vJ5sP/4uOSz2hxO0jQxzMr4wpiQ6NZ8tX/UGat8EuutZ8dYMfe6jM6RqNR4XZ3PHTr3JFxzL7k9AVOq9USGRmJoiisXPk3MjNHkJqadtrjAFas+As33HAj5557AV9//SXPPruSOXNupLGxkf/936epra2lvLyMK6+8nOHDM/j97xf3WkEAKQoiANmcTZSYD1NiLqPEUkqJuQyz49RBPMEaHQlh8STo41p/hcWRoI8nNjS61+5xt7gdJz7oW1o/6M0nffBbTnrs8rh65ZwnC9boiA2NwRQaiyk0BlNoTOvjsBgigyN8ei9fURR2Vn/P+qKPqGuuxxCkZ2b6DCYlnYdGrcGjeAjWBlNm8U9R8LeWlhaWLl1CWFgYixb9rsvHFRUV8dJLL/CPf7yIoigEB4eQmZnFVVddwx/+8BBut5vrr5/rs9xSFES/5nA7OGypoMRcSomljEPmwxy117bZJzI4ggmmsaQZhxAZEkFN01GONFVzxFZNubWCEsvhNvtr1Vriw0zHikQcw20p2Kwt7Z5fAVrcLZhbrMc+5C1tPvRb3I5O82tUGsJ1RpL1iRh1BsJ1RsKDjYTrjBh1BoLUZ/ZfUFEUlGAnB6vLqbHXctReS03TUcqtlafsq1VpiDlWKEyhMcSGnfhzTEg0GnX3v10WN5by1v4NFJtL0Kg0TE2dwrS0qYQFhXr3aXF4iAuJp9xWhtPtJEgT1O3zdcfsSzK69K3+ZL01ollRFB58cBHZ2edw0023ntGxaWlp3HLLAkaPHsvBg0UUFOxi//5CHA4H//M/f6Oq6gi//OVdXHXVz1Cr1Xg8nh7nPZkUBdFvuD1uKmxVrQXAXEaJ5TCVtio8yol/9GHaUEZFZ5EWPoQ0Ywpp4UOICA7v9DWPNtdxxFbNEVvVsWJRxZGmmhMfpMVnllOFCqPOQGxoTOuHvPfXf37oGwnThvb67R2TyUhN+IkPLkVRMDus1NiPtikUR+11VNuPUtV06i0UFSqiQ6JOKRam0FhiQ6PRadq//13XXM/6oo/4tiofgAmmscxMn4EpLKbNfuU1Vla89QP1EQraeA+VTVWkGlN68V3o37Zu/Zz8/H/jcDj46qvtANx55y8YO3b8aY+9995fs3z5MhwOBw6Hg//+7/tJTU3jxRef58MP30Or1XLbba3LDYwbdxZLljzCX/+6qs1SBT0hcx8NknlO+trp8iqKQo39aOuHv/kwJZbDHLaU4zzpFkuQOoghxmSGegtAKrGh0b3yIetRPNQ3N3KkqRqHtgmLpbnDfXWaICJ04a3f9IONGIL0fu1ieab/FmzOJm+hqLHXtSke7d12A4jQhWMKiznp1lQ0FbYqPi3dgtPjYogxmWszriAzKv2UY/+9r4bn399Ni8ONxnQY3bAfuXHk9fxX0rnd/pn7SiD9Pwu4WVKFOFlrQ/CxAmA+TKmljCaX3btdrVKTpE8gLTzl2FXAEBL18T26xdEZtUpNTGgUMaFRAfVB0B36oDD0QWGkhQ85ZVuzq4Wjx68uTv7VdJSihkMcaGh7GRWhM3Jl+s84PyH7lMLoURTe+6KY97YdQhekZtr5qXxc0Ajgt8ZmceakKIhe1+xqZteRMnYd3nfsKqCMhpbGNvvEhcYyOmYEQ8NTSQtPIcWQ1OEtC+E7IdpgUoxJpBiTTtnm9Liotdd5C4ZKpeKChHMI0Qafsq+9xcXf39/Nd/uPEhsRwi9mjcMUGco/vykGRTVoG5sDkRQF0WucbiebD3/BxyWf0ew+0XAboTMyPnbMSVcBKYQFhfkxqeiKILXW23OrM1V1TTz11i4qa5sYlRbFnVePwRjWWuDjooxYWvSUWyvwKJ5BM7I5kElRED2mKAr/rt7F+qIPqW2uRx8UxtWZlxEXlMDQ8CFEBkf4O6LwkR8O1vLs+h9panFx6TkpzLkkA436xAf/sMRw/m010hxSSV1zPbGhMZ28mugPpCiIHjlkbu2aeLCxbdfEtKS4AX2ffrBTFIV/fl3Kui1FaNRqFswYxaRxpy6fm5YYzs6CcKCSMkuFFIUAIEVBdEt9cwPriz5iR9V3QMddE8XA0+J089JHe/l6dxVRxmDuuWYcw5Pa7xY8NCEczzetvVzKrBVMiBvXl1FFN/isKHg8HhYvXkxhYSE6nY7HH3+ctLQTw7xfeOEFPvjgA1QqFXfeeSc5OTnebUVFRcyePZvt27cTHHxqo5bwn2ZXC5tKP2dT6VacHmenXRPFwHO00c7Tb/1AabWVjOQI7rlmLBGGjv+PpiUa8TSdKAoDXV/NkpqX9xKXXnohiYnDev1n8FlR2LRpEw6HgzVr1pCfn8+yZct45plnADCbzeTl5bFx40bsdjszZ870FgWr1cqTTz7Z5cmjRN/wKB6+rtzJhoP/pNFhIUIXzlXp13BeO10TxcC0t6SeVe8WYLU7mXJWEjfmZBGk7fzvPtlkQKuEoHaFcHgQ9UDy9Syp8+ff6rOu1D4rCjt37mTy5MkATJgwgYKCAu+20NBQkpKSsNvt2O1272AkRVF45JFH+PWvf83dd9/tq2jiDO2rL+Lt/Rs4bK0gSB3Ez4ZeSk7aRQRLF9IBzenycLjaSnGlmYMVjXy9uxqVCuZfPoKLz07u0mtoNGqSYvRU2Yw0aGuwOmwYdHofJ/e/nsyS+sQTi2lsbMRsbuTJJ//CM8+soLq6isbGRi644L/4+c/v4oknFjNr1tUUF5fx5ZfbaGlppry8jBtvvIXp06/sUXafFQWr1dpm2LVGo8HlcqHVtp4yMTGRGTNm4Ha7Wbiwdcj2008/zYUXXsjIkSN9FUucgaP2Ot4+8D7f17QW9HPjs7k6fRpRIZF+TiZ6m8ejUFlr42ClmUOVFg5WmimrtuL2nJjwINKg486rx5I15Mz+/pNNBioajagjaiizVjAyOrO347fr7QPv8131D2d0jEatavMz/6ez48YxK+OK075OT2ZJBZg48RzmzLmRysoKxowZx+9+9wgtLS3MmjWdn//8rjb72mxW/vKXpzl8uJQHHvjv/lsUDAYDNpvN+9jj8XgLwtatW6murubTTz8FYMGCBWRnZ/Pee++RkJDAW2+9RU1NDbfddhuvvvpqp+eJigpDq+3+qNeOhnr3R32VtcXlYP3ej1m/ZyNOj4sRsencMuE6MmKGntHryHvrOz3JqygK1fV29pXWs/9wA/tK6zlY3oC95cQ03lqNmuHJEWSlRpE5JJKs1CiSTQbU6jOfYmTksGi+3tbaEN2g1PXZex1WrkPTjbydHRMWqus0v9EYQlhY6z4tLS089NBD6PV6li17osPprXU6LVFRYd7XDQkJYty4UZhMRkJDk1m3bj/Lli3GYDDgdDoxmYyEhAR5zzd+/FhMJiPh4Rm43a4ev78+KwrZ2dls3ryZ6dOnk5+fT1ZWlndbREQEISEh6HQ6VCoVRqMRs9nMJ5984t3nkksu4cUXXzzteerrm7qdMZCmN+iLrIqi8H1NAev2b6C+pYEIXTjXZMzgnPgJqDyqMzq/vLe+c6Z5zTYHxZVmiivNHDpi4WCFGavd6d2uAhJj9WRnGRmWGM6wxHBSTIZT2gtqa63dyhoVFoRyrLF575FiLojpm/d6WvJlTEu+7IyO6cp729l2i6WZpiYH1dVmFi261ztLal1dx59TDoeL+vom7+s2Nzsxm5upqbHw5ptvoNEE87vf3U9Z2WHWrl1LdbWZ5man93x2u5OaGgstLS243Z4u/9vo87mPcnJy2LZtG3PnzkVRFHJzc1m9ejWpqalMnTqV7du3M3v2bNRqNdnZ2UyaNMlXUUQXHLFV8ea+99hbvx+NSkNO6kVMGzq13SkNxJlRFIVmhxtzk4NGqwOzzUGjrfV3Y1gQSbF6EmP0RBp0PZ7sz97iouSIheIjZoorLRRXmKk1t53sLyY8hJFpUQxLNDI8MZzUeCOhwb7rnZ5sMqC0hKFStJQPgh5I0LNZUk82ceK5LF78ELt25RMSEkJKyhCOHq3xRWQvmSU1QL4h+iqr3dXMh8Wf8HnZNjyKh9HRI7gu6yriw0w9et3B8N46XW4aT/qAb7Q5MFvbPm60tdBoc+Bwnn7O+9BgLUkxYSTG6EmMbf09KVZPbHhIm9s2x/M6XR7Kaqzeq4DiSguVR22c/B/aEBrE8KRwhiYYj/0eTri+7zoImExGqqvN3Pe3f0Hmdghr4C9THuvztRW6ajD8uz35+PbI4LVByqN42HHkO94p+gCLw0psSDTXZl7JuNjRfl/esb+wt7jYW1JPRa3txAe91eH9xt/U0vlKahq1CmNYEInReiIMOsL1OiL0J343hulotLVQebSJiloblbVNHDpioajC3OZ1grRqEqLDWq8oosNwKrD74FEOV1txnbR0ZHCQhqwhka23gJLCGZZgJCYixO9/nyqViiFxBorMBrShdVTaqkgNHzxrKwQaKQqDUKmljLWF6yk2lxCkDuKKYZdzaeqUfvvtra94PAolVRYKDtbyY3EdRRXmdnuiGEKDiAoPZqjeSIReR4Q++MQHvkF37Dkd+tAg1Gf4gexye6hpsFPhLRQ2Ko7aOFLbxOHqE/f0NerWD9rjbQDDEo0kxui71RDcF5JNBvaXnhjEJkWh/5KiMIhYHTbeO/hPtld8g4LC2aZxzMq8guiQKH9H8wuny82ROjvfF9fx5a4Kdh+q9zbAqlStk7mNGRrN8KRwIg2tH/zGsCC0Gt8N1tNq1K23j2L0TOTELTyPolDX2ExlXRPJCeEYdZrTDhzrT1JMejx7W3sgDYaRzYFMisIg4FE8fFH+FRsOfkyTy06CPp7rM6/qs/7i/mZvcVFZ20TF0dZv3sf/XNNo5+QWtShjMJPHJzJ2eAyj0qIwhPafKye1SkVsZCixkaEBdd/7uBSTAaXJIGsrBAApCgPcgYZi1u57l3JrJSGaEK7NuIILUyb5bEUzj0ehptGOucXdo+7C3dXscFFR20TlsQJQUdtEvaXllP0MoUFkpkSSFBPGiGExpMSEkRQT5vf77wNVskkPioYgdzjl1kpZW6Efk6IwQDW0NPLugQ+9s5hekHAOV2f8jHBd7wwccro8VNW13vdu/QbeRGWtjSN1TW0aP/0tyhjMmGHRJMaEkXSsN09iTJh3ERgIrB4ngSpEp8UUGYLNYsCpbaTWXi8z6vZTUhQGGJfHxebDX/DRoU20uB2kGpOZnTWTYRFdH2J/shanm4qjrR/8FbU2Ko+2fvhXN7S99QKtvV9STAYSY/SYYsKwNznbf1Ef0gWd6KmTEB3m0/734sykmAz8YDEQFNXariBFoX+S/zEDyO7aQt7cv57qpqMYgvRcm3ElP0k6t9uX6TsLq3nxw73Y/6PrpT5ES0ZyhLcf/fG+9dHhwd7bL/LtW/ynFJOB76tO9EA6W9ZW6JekKAwAR+11vLV/A7uO/ogKFRem/BdXDLus2+sgu9we1n1exMYdh9EFqbkkO5nkWL135K0xLEjuvYszlhJnwNN0rAeSpdzPaURHpCgEMIfbwcaSzXxSugWXx0V6xDBmZ11NijGp269ZZ27m/9b/yIHyRhKiw7jnmrEkmwynP1CI00gx6cGlI8gTRpm10t9xRAekKAQgRVHIryngrZMmrpuVMYOJ8RN69A3+x+I6nn3vR6x2J+eNiuOWaSPlnrzoNXFRoWg1alTNETSoK7E4rBh18oWjv5H/8QGm0lbFm/vWU1h/oNcmrvMoCu9vO8T6L4pRq1XcmJPFJdnJcotI9CqNWk1yrJ4jjWGow6DcWjloxsoEEikKAaLJaeet/RtOTFwXM4LrMns+cZ2lycHzG3ZTUFxHTHgwd83seBF2IXoqxaTncLmRYOjTBXdE10lRCADFjSU8vz2PxmYzsSHRXJd1FWNjRvX4m/yB8kaeebeAeksL49NjuP2K0f1qFK8YeJJNBpT9x3ogycjmfkmKQj9ndzXz4o+vYW6x9NrEdYqisOnbMtZuPoBHUZg1ZTjTf5J2xpO3CXGmUuL0KC1haAiSOZD6KSkK/dxb+zdQ11zPrNE/Y2rCxT1+PXuLi9Uf7uHbwhrCw4JYeNUYRg2N7oWkQpzeEJMBUKFzRVLVVIPD7UQ3yGfn7W+kKPRjPxzdzZeVOxhiSOK60dOpr7P36PXKqq2sfOcHqurtZKVEsPDqsUQZZWU10XfC9ToMoUG4rAY8kTVU2o6QFj7E37HESaQo9FNWh41X965Dq9Jw8+i5aDU9+6va9kMleR8X4nB5mHZ+KtdeOByNWiYkE31LpVKRYtKzvz4MXWRrY7MUhf7FZ0XB4/GwePFiCgsL0el0PP7446SlnZh/54UXXuCDDz5ApVJx5513kpOTg8Vi4f7778dqteJ0Ovnd737H2Wef7auI/ZaiKLxe+DYWh5WZ6dNJMiR0+7UcTjevfrKPf+2qJDRYy71XjeHsrJ71WBKiJ1LiDBTuOT6yWQax9Tc+KwqbNm3C4XCwZs0a8vPzWbZsGc888wwAZrOZvLw8Nm7ciN1uZ+bMmeTk5LB69WouuOACbr31Vg4ePMiiRYt45513fBWx39pR9R35NT+QHjGUqalTuv06VfVNrHqngMPVVlLjDdx9zTjiIkN7MakQZy7FZEDZaUCFShqb+yGfFYWdO3cyefJkACZMmEBBQYF3W2hoKElJSdjtdux2u7dr5a233opO1zqlsdvtJjh48N3vrm9uYO2+d9FpdNw8ek4PJrOr4cUPd2NvcXPhhCTmXZpJkNY3aygIcSZSTAZQNIQqkZRbK2RthX7GZ0XBarViMJwYwq7RaHC5XGi1radMTExkxowZuN1uFi5cCEB4eOslZU1NDffffz8PPfSQr+L1S4qi8MqeN7G7mrlhxCxiQ898auE2k9lp1SyYMYpJ4xJ9kFaI7kmO1aMCVM3htITWc9ReR1xYrL9jiWN8VhQMBgM2m8372OPxeAvC1q1bqa6u5tNPPwVgwYIFZGdnM378eAoLC/n1r3/Nb3/7W84777zTnicqKgxtD74Bm0y9s+hMb/h4/xb21u/n7MQxzDzr0lMGp50ua22jnf99+Vv2HKoj2aTnwVvOIy3Rf6OT+9N7ezqBlBUCK297WRNi9Zgb9BAKFnU9Y0zD/JCsfYH+3vaUz4pCdnY2mzdvZvr06eTn55OVleXdFhERQUhICDqdDpVKhdFoxGw2c+DAAX75y1/y17/+lZEjR3bpPD1Z8rE/zflf3VRDXv5bhGlDuW74TI4etbbZfrqsPx6q47n3fsTS5OTckXHc+rORhGpVfvv5+tN7ezqBlBUCK29HWROjw6g6oic4EX4sLyI9pH9MdzEQ3tszOb49PisKOTk5bNu2jblz56IoCrm5uaxevZrU1FSmTp3K9u3bmT17Nmq1muzsbCZNmsTdd9+Nw+HgiSeeAFqvNo43Tg9kHsXDy7vX4vA4uWnU9UQGR5zBsQrvbz/E+n/JZHYicKSY9Pz74IkFd0T/4bOioFarWbJkSZvn0tPTvX++7777uO+++9psHwwFoD2bSrZQbC5hYtxZTIyf0OXjLE0Onn9/NwUH64gOD+aumWNJT+p6QRHCX1JMBnDpCFEZZA6kfkYGr/lZmaWC94s3EqEzMnvEzC4fV1TeyDPrC6gztzB2eDR3XDlGJrMTASMlrrUTis4VSaNSJmsr9CNSFPzI6XHx8p41uBU380ZehyFIf9pjFEXh051lrPmsdTK7a6YMZ4ZMZicCTFxkKDqtGpfFAMdGNo+Kzjr9gcLnpCj40YfFn1BurWRS0vmMjR112v3tLS5Wf7SXb/dWYzw2md1omcxOBCC1WkVirJ6K2lC0ka1XzFIU+gcpCn5ysPEQn5R8TkxINLMyZpx2/0OVZh7/x7dU1TWRmRLBnTKZnQhwQ0wGSvcZ0SKNzf2JFAU/aHa18I/dawC4efQcQrQhne5fUFzL028X4HC6mXZeKrMuHI5WIyNARWBLMelRfgglSKWjzCpzIPUXUhT84N2iDzlqr2Vq6hQyIjsftFPb2Myz639EURTuuWYcE0fIZHZiYEiOa11bIUyJpspWJWsr9BPydbOP7a4t5F/lX5Koj+fKYZd3uq/L7eGZ9QXYml0slIIgBpgUU2tvI1VzBAoKlbYjfk4kQIpCn2pyNvHKnjdRq9TcMnruaZfVXPvZAQ5WmPnJmAQuOz+t032FCDQReh3hYUE0NbTO3CvjFfoHKQp9aO2+9TQ6zEwfmsMQY3Kn++7YW82mnWUkx+q5+fIRMkJZDEjJJgPmo8eKgjQ29wtSFPrIv6t3saPqO9LCh3BZ2kWd7nukronVH+4hOEjDXTPHEqyTKa/FwJRiMqDYZW2F/kSKQh9obLHwRuHbBKmDuGXUHDTqjj/kW5xuVr3zA80ON7f8bARJsacf0CZEoEqJ04OiwaiJpsxaiUfx+DvSoCdFwccUReG1veuwOZuYmT6deH1cp/u/unEfZTU2Lj47mQtGd38ZTiECwfHG5mBnFA63g6P2Wj8nElIUfOzLym8pqN1DVlQGU1J+0um+/9pVwRc/VJKWYGTu1P4xlbAQvpR0bMEdp7W1OByWxma/k6LgQ7X2OtbtX0+IJoT5o67vdMnBw9VWXtm4j7BgLXfPHEuQVv5qxMAXHKQhLiqUxprWAZzSruB/8snjIx7FQ96etbS4HVyfdRXRIVEd7mtvcbHqnR9wujwsuGIUpsjQPkwqhH+lxBloagwDpCj0B1IUfOTzw1+wv+EgZ8WO4fyEiR3upygKqz/aS1W9nWnnp3J2pgxQE4PL8bUVDBoj5XL7yO+kKPhApa2K9Qf/iSFIzw0jr+10jMGnO8v4dm81mSkRzJoyvA9TCtE/pJhae9jpiaHRYcHsCIzlMAcqKQq9zO1x8/LuN3B5XNww8tpOFw4pqmhkzWcHMIYFcefVY2WSOzEoHe+BhD0cgHKLTI7nTz77FPJ4PDz66KPMmTOH+fPnU1JS0mb7Cy+8wKxZs7j22mv55JNPAGhububee+9l3rx5/PznP6eurs5X8Xzmn4c+pdRSzvkJE5lgGtvhfla7k/97twCPR+GOq8bINNhi0DJFhqILUtPU0HrFIO0K/uWzorBp0yYcDgdr1qxh0aJFLFu2zLvNbDaTl5fHG2+8wYsvvkhubi4Ar7/+OllZWbz22mvMnDmTVatW+SqeT5SYD/PPks+ICo7k+qyrOtzPoyj8/f3d1JpbuPqnwxgjC+WIQUytVpEcq6f2iA6QouBvPisKO3fuZPLkyQBMmDCBgoIC77bQ0FCSkpKw2+3Y7XbvPfeTj5kyZQpffvmlr+L1OofbyT92r8GjeLhp1PWEajvuQfTRVyXsKqplzLBorpg0tO9CCtFPJZsMuJtDCFYHy8R4fuaz9RSsVisGw4n76RqNBpfLhVbbesrExERmzJiB2+1m4cKF3mOMRiMAer0eiyVwGpw2HPwnVU3VXJgyiZHRHQ8821tSz9tbDxJlDObnV46WtZWHSjXWAAAgAElEQVSFoHUVNlARoYmlqqkCh9uBTqPzd6xByWdFwWAwYLPZvI89Ho+3IGzdupXq6mo+/fRTABYsWEB2dnabY2w2G+Hh4ac9T1RUGFpt9yeMM5mM3T72uB+r9/HZ4X+RaIzj9vNnE6xt/x9zvbmZ597fjVql4sFbziM97cxuG/VG1r4USHkDKSsEVt6uZB2TaYJP9xNGDArlNAWZSY7pfAEqXxlo7+2Z8llRyM7OZvPmzUyfPp38/Hyysk4syh0REUFISAg6nQ6VSoXRaMRsNpOdnc2WLVsYP348W7duZeLEjvv3H1df39TtjCaTkZqanl2N2F3NrPjmJVSouDFrNub6FqDllP3cHg/L38inwdLCnEsyiDUEndG5eyNrXwqkvIGUFQIrb1ezGnStd7Kb6wxghJ2HdhPpifV1vFMMxPe2s+Pb47OikJOTw7Zt25g7dy6KopCbm8vq1atJTU1l6tSpbN++ndmzZ6NWq8nOzmbSpElMnDiRBx54gBtuuIGgoCCWL1/uq3i95q39G6hrrmfa0KkMi0jtcL93/1XM3tIGsrNMXHbukD5MKET/Fx6mI1yvo6GqtSjsbyhiauoUf8calHxWFNRqNUuWLGnzXHp6uvfP9913H/fdd1+b7aGhoTz11FO+itTrfji6my8rdzDEkMTPhk7tcL9dRUf54MsSTJEh3DZ9pCyYI0Q7hpj0/HjIQUpINAcaivEonk7nCxO+Ie94N1kdNl7duw6tSsPNo+eiVbdfX2sbm3l+w260GjV3zxxHWIgsTC5Ee5KPDWJL1KVidzVLLyQ/kaLQDYqi8Hrh21gcVq4YfjlJhvbXPXC5PTyzvgBbs4t5OZmkJQROA5YQfe34yOYwVzwA+xqK/Bln0JKi0A07qr4jv+YH0iOGdnrfc+1nBzhYYeYnY+K58KykPkwoROBJiWsd0ewyt84ovL9eioI/SFE4Q/XNDazdtx6dRsfNo+d0eM9zx95qNu0sIylWz82XSzuCEKeTFKNHpYKaaoW40FgONBzC7XH7O9agI0XhDCiKwit73sTusnNtxhXEhsa0u9+RuiZWf7iH4CANd88cS7Cu++MohBgsdEEa4qPCOFxjIyNyOM3uZpnywg+kKJyBf5V/yd76/YyOGcGkpPPb3cfhdLPqnQKaHW5umTaCpFh9H6cUInClmPTYW1wkhbR2794nt5D6XJeKwowZM/j73/9OTU2Nr/P0W9VNNbxz4APCtKHcOPK6Dm8HvfLJPspqrFx0djIXjGm/AVoI0b6UuNbG5qCW1sWm9jcc9GecQalLReG5556jpaWFm2++mTvuuIN//vOfOJ1OX2frNzyKh5d3r8XhcTJ3xDVEBke0u98Xuyr5YlclafFGbpia0ccphQh86cmt/7cqj7iJC4ulqKFY2hX6WJeKQnJyMvfccw8fffQR119/PUuXLuWnP/0pTzzxBPX19b7O6HebSrZQbC5hYtxZTIyf0O4+ZdVWXtlYSGiwlruuGUtQD+ZjEmKwGp4YjlqlYn9ZI5mR6TS7WzhsLfd3rEGlS0XBZrPx9ttvc8stt7B8+XJuuOEG1q1bx9ChQ1mwYIGvM/pVmaWC94s3EqEzMnvEzHb3sbe4WPluAQ6Xh9tnjCIusuNps4UQHQsN1jIkzsChSjPp4a0T4u2vl1tIfalL01xMnTqViy++mF/84hece+653ufnzZvH9u3bfRbO35weFy/vWYNbcTNv5HUYgk5tNFYUhZc+2ktVXRPTzkvl7CyTH5IKMXBkpkRQUmUh2BEHtA5iy0m7yL+hBpEuXSls2rSJ+fPnc+6552KxWLyL36hUKlauXOnTgP70YfEnlFsrmZR0PmNjR7W7z2f/LmfH3moyUyKYdeHwPk4oxMCTOSQSgIojbuLDTNKu0Me6VBSeffZZ/vznPwNgt9tZtWoVK1as8GkwfzvYeIhPSj4nJiSaWRkz2t+nwswbn+7HGBbEnVePRauRHr5C9FTGscbm/YcbyIxKp8XtoNQi7Qp9pUufYps3b+b5558HIC4ujtWrV7Nx40afBvOnFreDf+xeA8DNo+cQog05ZR+r3ckz7xbg8SjccdUYoozBfR1TiAEpyhiMKTKEA+WNZES0Xn3vl3mQ+kyXioLL5aK5udn7eKB3R333wAcctddySepkMiJPXf3Joyj8/f3d1Jqbueqnwxgz9MxWUBNCdC4zJRJbs4twT+tYHxnE1ne61NA8d+5cZs2axSWXXAK0Lqc5b948nwbzlz21+9ha/iWJ+niuHHZ5u/t89FUJu4pqGTM0iiv/a2jfBhRiEMhMiWB7wREqq9wkhMVR1Ng6D5JGLV29fa1LReHWW29l4sSJ7NixA61Wy//8z/8wevRoX2frc03OJl7Z+yZqlZpbRs8lSHPq2geFpfW8vfUgUcZgfn7VGNRqmehOiN6WmdLa2Ly/rIHMrHT+Vf4lpZYyhkWk+TnZwNel20cOh4MjR44QHR1NeHg4e/bs4W9/+5uvs/W5tfvW09DSyPShOQwxJp+yvdHawv+t/xEVKu68egzhYTo/pBRi4EuICUMfoj02iK21XUFuIfWNLl0p/PrXv6axsZHS0lLOOeccvv76a7Kzszs9xuPxsHjxYgoLC9HpdDz++OOkpbVW+T179pCbm+vdNz8/n5UrV5KRkcFvf/tbFEUhIiKC5cuXExraNwPB/l29ix1V35EWPoTL2ukT7fZ4ePa9H2m0OZh9cYb3m4wQovepVSoyUyLJP3CUuKARQOs8SJdziZ+TDXxdulIoLCzk5ZdfJicnh9tvv53XX3+d8vLOu4ht2rQJh8PBmjVrWLRoEcuWLfNuGzVqFHl5eeTl5TFv3jwuu+wypkyZwksvvcTPfvYzXn31VTIzM1m3bl3Pfrouamyx8Ebh2wSpg7hl1Jx271u++69i9pY2cHZmLJefN6RPcgkxmGWmHJsHqcpFgj5exiv0kS4VhZiYGFQqFcOGDaOwsJAhQ4actgfSzp07mTx5MgATJkygoKDglH2amppYsWIFv//974HWYmE2mwGwWq1otV26kOkRRVF4be86bM4mZqZPJ14fd8o+u4qO8sGXJZgiQ1gwY5QsmCNEHzjRrtBIVuRwHB4nJZbDfk418HWpKGRmZvLYY49x/vnn89JLL/Hcc8+hKEqnx1itVgwGg/exRqPB5XK12WfdunVMmzaN6OjWLp0JCQm8+uqrzJgxg61btzJt2rQz/XnO2JeV31JQu4esqAympPzklO21jc08v2E3Wo2au2eOIyzk1MZnIUTvS0swotWoWxubo9IB2CfzIPlcl76K/+EPfyA/P5+MjAzuvfdevvzyS5YvX97pMQaDAZvN5n3s8XhO+ea/YcMGnnrqKe/jP/3pTyxdupTJkyfz+eef88ADD/Dcc891ep6oqDC03ZyRtNpWy1sH3iM0KIRfTfp/xOrbTontdHl48rXvsDW7uOe6szhnnH/XWTaZjH49/5kKpLyBlBUCK29Pso5Ii2JPcS1npZwNBVBiK/H5zz5Y3tuOdKkoXH/99bzzzjtA6+R4U6dOPe0x2dnZbN68menTp5Ofn09WVlab7RaLBYfDQWJiove58PBwjMbWHzIuLs57K6kz9fVNXfkRTuFRPDxT8A+aXS3MHzUbpSmImiZLm31e+2QfhaX1/GRMPNnp0dTUWDp4Nd8zmYx+Pf+ZCqS8gZQVAitvT7MOjTfw48Fa9hSaSdTHs7fmAJVV9WjVvrm1PJje244KSpfe2djYWL799lvGjx+PTte1bpg5OTls27aNuXPnoigKubm5rF69mtTUVKZOnUpxcTHJyW27fT7yyCMsWbIEj8eDoig8+uijXTpXd3x++At21+znrNgxnJ8w8ZTtO/ZWs2lnGUmxem6+fKS0IwjhB8cbm/cfbiQrIZ0ttipKzGWkRw71b7ABrEtF4YcffuCmm25q85xKpWLPnj0dHqNWq1myZEmb59LT071/Hj9+PKtWrWqzPSMjg5dffrkrkXpsS9l2woMN3DDy2lM+8I/UNbH6wz0EB2m4e+ZYgnUyilIIfzi+Etv+sgZyRqazpWw7+xuKpCj4UJeKwldffeXrHH1uwdibSIyLJqg5rM3zDqebVe8U0Oxwc8eVo0mKPXUNBSFE39CHBJFs0nOw0syw8NYr+n31RUwbevpb2KJ7ulQUnn766Xaf/8UvftGrYfpSangKJqORmua29+Re+WQfZTVWLjo7mQvGJPgpnRDiuMyUSMprbNTXKyTpEzjYWILT4yLIR+0Kg90ZLwDgdDr57LPPqK2t9UUev/piVyVf7KokLd7IDVMz/B1HCMHJ7QqtXVOdHiclZhmv4CtdKrX/eUVwzz33cNttt/kkkL+UVVt5ZWMhocFa7rpmLEHd7OYqhOhd3qJQ1sikocPZUraN/fVF7U5rL3quW0uF2Ww2KioqejuL39hbXKx8twCHy8PtM0YRF9k38y0JIU4vJjyEKGMw+8saSD9WCPY1yCA2X+nSlcIll1zi7aGjKAqNjY3cfvvtPg3WVxRF4aWP9lJV18S081I5O8vk70hCiJOoVCoyUyL4Zk81TVY1yYZEihsPSbuCj3TpHc3Ly/P+WaVSER4e3mYKi0D22b/L2bG3msyUCGZdONzfcYQQ7chMieSbPdXsK2sgM3I45dZKDjWWkhkl/2d7W5duH9lsNv785z+TnJyM3W5n4cKFHDwY+Jdv+0rreePT/RjDgrjz6rFoNd26myaE8LGT2xWyjs2DJOs2+0aXPgUffvhhZs6cCbQOQLv77ru9M5sGKqvdyZMv78DjUbjjqjFEGYP9HUkI0YEUk4EQnYYDZY1kRA5HhYr9MjmeT3SpKNjtdi688ELv40mTJmG3230Wqi+8/HEh1fV2rvrpMMYMjfZ3HCFEJ9RqFRnJERypa8Lt1JJkSOCguQSnu/Mp/MWZ61JRiI6O5vXXX8dms2Gz2Vi7di0xMTG+zuZTTc1O/mt8Ilf+11B/RxFCdMHxW0gHjt1CcnlcHDKX+jnVwNOlorB06VI+//xzfvrTn3LJJZewZcsWnnjiCV9n86nfzD2bB285D7VaJroTIhCcWHSngczIY+srSNfUXtel3kdJSUn88pe/ZPTo0VgsFgoKCkhIkCkghBB9Z1hSOBq1iv1ljVw5efSxdoUiGJbj72gDSpeuFP785z/z5z//GWhtX1i1ahUrVqzwaTAhhDhZcJCGtAQjJUcsaAgmxZBIsblU2hV6WZeKwueff87zzz8PtC5+s3r1ajZu3OjTYEII8Z8yUyJwexSKK8xkHmtXKJZ2hV7VpaLgcrlobm72PnY6pTILIfqet12hvJHMyNaBa/vqZbxCb+pSm8LcuXOZNWsWl1xyCQBbt27lxhtv9GkwIYT4TxknLboz9dwRre0KMoitV3WpKNxwww04nU4cDgfh4eFcd9111NTU+DqbEEK0Ea7XER8dRlF5IyGaEFKMSRxqLMXhdqLTBPk73oDQpaKwaNEiGhsbKS0t5ZxzzuHrr78mOzu702M8Hg+LFy+msLAQnU7H448/TlpaGgB79uwhNzfXu29+fj4rV67knHPOYfHixZSVleF0OnnkkUcYP358D348IcRAk5kSwRe7KimrsZIZOZzDlnKKG0sYES1roPSGLrUpFBYW8vLLL5OTk8Ptt9/O66+/Tnl5eafHbNq0CYfDwZo1a1i0aBHLli3zbhs1ahR5eXnk5eUxb948LrvsMqZMmcILL7xAZmYmr732Go899tiAmF9JCNG7ZB4k3+pSUYiJiUGlUjFs2DAKCwsZMmTIaRubd+7cyeTJkwGYMGECBQUFp+zT1NTEihUrvPMoffHFFwQFBbFgwQJWrVrlPV4IIY7LOmkQW3rEMFSo2CfzIPWaLt0+yszM5LHHHuOGG27gN7/5DdXV1SiK0ukxVqu1zfTaGo0Gl8uFVnvilOvWrWPatGlER7fOPVRfX4/ZbOaFF17g3Xff5cknn+RPf/pTp+eJigpD24NV0kwmY7eP7WuBlBUCK28gZYXAytvbWWNjDUQagimqMJOaaGJY1BAONZYSHhVMsFbX49cfzO8tdLEoLF68mO+++46MjAzuvfdevvzyS5YvX97pMQaDAZvN5n3s8XjaFASADRs28NRTT3kfR0ZGens4XXzxxTz33HOnzVZf39SVH6FdJpORmhpLt4/vS4GUFQIrbyBlhcDK66us6Unh7NxXw96iGoYZh3KwvpRvigoYGZ3Zo9cdTO9tRwWlS7ePNBoN55xzDgBTp07l4YcfJisrq9NjsrOz2bp1K9DakPyf+1ssFhwOB4mJid7nJk6cyJYtWwDYsWMHGRnScCSEOFWbyfEij7cryC2k3uCztexycnLYtm0bc+fORVEUcnNzWb16NampqUydOpXi4mKSk5PbHLNw4UIefvhh5syZg1ar5cknn/RVPCFEAMvwtis0ct2IocfaFaSxuTf4rCio1WqWLFnS5rn09HTvn8ePH8+qVavabI+MjOTpp5/2VSQhxACRGm9Ap1Wzv6yBUO0IUo0plJgP0+J2EKzpebvCYCbrTwohAo5Wo2Z4UjjlNTZszU4yo4bjVtwUN5b4O1rAk6IghAhImSmRKECRzIPUq6QoCCECUuaQE4PY0iOHoVapZRBbL5CiIIQISOlJEahUsP9wA6HaEIYYkzl0rF1BdJ8UBSFEQAoN1jIkzsDBSgtOl4esyHQ8ioeDDYf8HS2gSVEQQgSszJRIXG4PJVUWMqOOr9sst5B6QoqCECJgnZgcr4H0iLTWdgWZB6lHpCgIIQKWd9Gdw42EaENaxytYDtPsavFzssAlRUEIEbCiw0OIjQjhQHkjHkUhK+pYu0LjIX9HC1hSFIQQAS0zJQKr3cmR2ibveAWZB6n7pCgIIQJa5knrKwyPGIpapZZBbD0gRUEIEdBOXoktRBtMmnEIpZYyml3Nfk4WmKQoCCECWmKsHn2Ilv1lDQBkRg3Ho3goknmQukWKghAioKlVKjKSI6hpaKbB2uJdX2HX0R/9nCwwSVEQQgS8jJMW3cmIGk5sSDTbK76hzFLh52SBR4qCECLgHW9s3lfWQJBay5wR1+BRPLxR+DYexePndIFFioIQIuANSzSi1ajYX9YIwOiYEUyMO4ticynbKr72c7rAIkVBCBHwgrQahiaGU1plwd7iAuDazCsJ0YSwvugjzI7uL3A/2PisKHg8Hh599FHmzJnD/PnzKSk50RNgz549zJ8/3/tr3LhxbN261bt9x44dXHjhhb6KJoQYgDJTIlAUOFhpBiAiOJyr0qdhdzXz1v4Nfk4XOHxWFDZt2oTD4WDNmjUsWrSIZcuWebeNGjWKvLw88vLymDdvHpdddhlTpkwBoLKykhdffBGXy+WraEKIAcg7iO1wg/e5yckXkGYcwrdV+eyp2+evaAHFZ0Vh586dTJ48GYAJEyZQUFBwyj5NTU2sWLGC3//+9wC0tLTwhz/8gcWLF/sqlhBigPJOjnesXQFArVIzd+Q1qFCxpvAdnG6nv+IFDK2vXthqtWIwGLyPNRoNLpcLrfbEKdetW8e0adOIjo4GYMmSJdx2223Ex8d3+TxRUWFotZpu5zSZjN0+tq8FUlYIrLyBlBUCK29fZTUBqQlGiivNREfr0WjUx84/ip81XsyH+z7ji6PbmD32ys5fZ5C/tz4rCgaDAZvN5n3s8XjaFASADRs28NRTTwFQVVXFt99+S2lpKStXrqSxsZH//u//5n//9387PU99fVO3M5pMRmpqAqMBKpCyQmDlDaSsEFh5+zrrsAQjpUcs/Ht3JUMTwr3PT024iO0lO3l398eMNowmXh/X7vGD6b3tqKD47PZRdna2t/E4Pz+frKysNtstFgsOh4PExEQA4uPj+fjjj71tDREREactCEIIcTLvPEiHG9s8H6IN4frMq3Apbt4ofAdFUfwRLyD4rCjk5OSg0+mYO3cuS5cu5cEHH2T16tV8+umnABQXF5OcnOyr0wshBqGTZ0z9T2eZxjI2ZhT7Gor45si/+zpawPDZ7SO1Ws2SJUvaPJeenu798/jx41m1alWHx2/bts1X0YQQA1RsRAiRBh37yxpRFAWVSuXdplKpmJ01k31fH+DtA+8zNnYU+qAwP6btn2TwmhBiwFCpVGSmRNJoc1DTYD9le0xoFNOH5WB12lhf9KEfEvZ/UhSEEAPKyesrtOeSIZNJ0iewreIbihoO9WGywCBFQQgxoBxvV9hbWt/udo1aww0jZwHwRuHbuD3uPssWCKQoCCEGlCHxBsL1On44WIeng15GwyOGMinpPCpsR/js8L/6OGH/JkVBCDGgqFUqxg+PwWxzUHKk4378V6dPxxCk54PiT6i11/Vhwv5NioIQYsAZnx4DwPcHjna4jz4ojGszr8TpcbJ237syduEYKQpCiAFnzLBoNGoV3xfVdrrfufFnkxWVQUHtXr6vOXV+tsFIioIQYsAJDdaSNSSSkiMWGqwtHe6nUqmYmzUTrUrDm/vfw+5s7sOU/ZPPBq8JIYQ/nZUew56SenYV1TLlrKQO94vXx3FZ2sV8eGgTd6x/ALUqML4rx+qj+fWEu9FpdL36ulIUhBAD0lkZsbzx2YHTFgWAy9Iuptx2hAZnAy5XYHRRNeljfFLApCgIIQak+Ogw4qNC+bG4DqfLQ5C24w/QIE0Qd4y7eVDNktqRwLhOEkKIbjgrI5YWp5t9h0+dIE+0T4qCEGLA6krXVNGWFAUhxICVNSSSEJ2G74uOyjiELpKiIIQYsLQaNWOGRVPT0MyRuu6v0jiYSFEQQgxoZ6XHAvD9gc4HsolWUhSEEAPauGPtCruKpF2hK6QoCCEGtAi9jmGJ4ewva6Sp2envOP2ez8YpeDweFi9eTGFhITqdjscff5y0tDQA9uzZQ25urnff/Px8Vq5cSUZGBg899BButxtFUViyZAnDhw/3VUQhxCBxVnoMxZVmCorrOG9UvL/j9Gs+u1LYtGkTDoeDNWvWsGjRIpYtW+bdNmrUKPLy8sjLy2PevHlcdtllTJkyhb/97W/cdNNN5OXlsXDhQv7yl7/4Kp4QYhA5K6O1XWHXaSbIEz68Uti5cyeTJ08GYMKECRQUnDoDYVNTEytWrOCVV14B4IEHHsBoNALgdrsJDg72VTwhxCCSGm8gwqBjV1EtHo+CWq3yd6R+y2dFwWq1YjAYvI81Gg0ulwut9sQp161bx7Rp04iOjgbw/n7w4EGefPJJVq5cedrzREWFodVqup3TZDJ2+9i+FkhZIbDyBlJWCKy8/SXreaMT+OSbUuqbXYxMi+5wv/6Styt8kdVnRcFgMGCz2byPPR5Pm4IAsGHDBp566qk2z3311Vf88Y9/5E9/+lOX2hPq67vf91jmOfGdQMobSFkhsPL2p6wjUiL45BvY8m0pMWFB7e7Tn/KeTk+zdlRQfNamkJ2dzdatW4HWhuSsrKw22y0WCw6Hg8TERO9zX331FU888QR///vfGTdunK+iCSEGodFDo9BqVOyS8Qqd8tmVQk5ODtu2bWPu3LkoikJubi6rV68mNTWVqVOnUlxcTHJycptjcnNzcTqd/O53vwNg2LBhLFmyxFcRhRCDSIhOy4jUKH4srqPO3Ex0eIi/I/VLPisKarX6lA/09PR075/Hjx/PqlWr2mx/7733fBVHCCEYnx7Dj8V17DpYy0UTkk9/wCAkg9eEEIPGWcdHN8stpA5JURBCDBpxUWEkxoSxu6QOZ4CssNbXpCgIIQaVs9JjcTg97C2VhXfaI0VBCDGoyMI7nZOiIIQYVDJSIggN1rKrqFYW3mmHFAUhxKCi1agZOyyao43NVBy1nf6AQUaKghBi0Dkr4/gaC9IL6T9JURBCDDpjh8egQtoV2iNFQQgx6ISH6RieHM6BcjNWuyy8czIpCkKIQWl8eiweRaGgWG4hnUyKghBiUPKObpZ2hTakKAghBqUhcQaijMH8cGzhHdFKioIQYlBSqVSMT4/B1uyiqKLR33H6DSkKQohB66z01rWbv5cJ8rykKAghBq1RaVFoNWp2FUnX1OOkKAghBq1gnYZRaVGU1diobWz2d5x+QYqCEGJQG+/thSRXCyBFQQgxyB3vmvq9dE0FfLgcp8fjYfHixRQWFqLT6Xj88cdJS0sDYM+ePeTm5nr3zc/PZ+XKlYwdO5bf/OY3NDc3ExcXx9KlSwkNDfVVRCGEIDYylORYPXtK6ml2uPwdx+98dqWwadMmHA4Ha9asYdGiRSxbtsy7bdSoUeTl5ZGXl8e8efO47LLLmDJlCqtWreKKK67gtddeY/To0axZs8ZX8YQQwmt8RgxOl4ddMheS764Udu7cyeTJkwGYMGECBQUFp+zT1NTEihUreOWVV7zHLFy4EIApU6bwl7/8hVtvvdVXEYUQAmjtmvrRV6Usfekb1GqVv+N0iSkyjIfnTyRYp+nV1/VZUbBarRgMBu9jjUaDy+VCqz1xynXr1jFt2jSio6O9xxiNRgD0ej0Wi+W054mKCkOr7f6bYjIZu31sXwukrBBYeQMpKwRW3kDIGh1j4MLd1ZQftfo7SpeZIkNJSAhHq+ndGz4+KwoGgwGb7cQCFh6Pp01BANiwYQNPPfXUKceEhIRgs9kIDw8/7Xnq65u6ndFkMlJTc/rC0x8EUlYIrLyBlBUCK28gZb3l8qyAytvTrB0Va5+1KWRnZ7N161agtSE5KyurzXaLxYLD4SAxMbHNMVu2bAFg69atTJw40VfxhBBCtMNnVwo5OTls27aNuXPnoigKubm5rF69mtTUVKZOnUpxcTHJycltjrnrrrt44IEHWLt2LVFRUSxfvtxX8YQQQrRDpQT4ytU9vXwaLJeKfS2Q8gZSVgisvIGUFQIrb8DdPhJCCBF4pCgIIYTwkqIghBDCS4qCEEIILykKQgghvAK+95EQQojeI1cKQgghvKQoCCGE8JKiIIQQwkuKghBCCC8pCvPHnpIAAAaZSURBVEIIIbykKAghhPAa1EWhqamJu+66i3nz5rFgwQLq6ur8HalDFouFO++8k5tuuok5c+bw3Xff+TtSl3zyyScsWrTI3zHa5fF4ePTRR5kzZw7z58+npKTE35FO6/vvv2f+/Pn+jnFaTqeT+++/n3nz5nHdddfx6aef+jtSh9xuNw8++CBz587lxhtvpLS01N+RuqS2tpYLL7yQoqKiXn3dQV0U1q5dy5gxY3jttdeYMWMGq1at8nekDq1evZoLLriAV155haVLl7JkyRJ/Rzqtxx9/nOXLl+PxePwdpV2drSPeHz3//PM8/PDDtLS0+DvKab333ntERkby2muv8fzzz/PYY4/5O1KHNm/eDMAbb7zBfffdx9KlS/2c6PScTiePPvooISEhvf7aPltPIRDceuutuN1uACoqKoiNjfVzoo7deuut6HQ6oPWbTXBwsJ8TnV52djaXXnopa9as8XeUdnVlHfH+JDU1lRUrVvDb3/7W31FOa9q0aVx++eXexxpN764j3JsuvfRSLrroIqD/fw4c9+STTzJ37lyee+65Xn/tQVMU3nzzTf7xj3+0eS43N5fx48dz8803s2/fPlavXu2ndG11lrWmpob777+fhx56yE/pTtVR3unTp/P111/7KdXpdWUd8f7k8ssvp6yszN8xukSv1wOt7/F9993Hr371Kz8n6pxWq+WBBx7gk08+abNEcH/09ttvEx0dzeTJk31SFFCEoiiKcuDAAWXq1Kn+jtGpvXv3KtOnT1c+//xzf0fpsq+++kr51a9+5e8Y7crNzVU++OAD7+PJkyf7MU3XHD58WLn++uv9HaNLKioqlGuuuUZ58803/R2ly6qrq5WLLrpIsdls/o7SoXnz5ik33nijctNNNykTJ05Urr32WqW6urrXXr9/fiXqI88++yzx8fHMnDmTsLCwfn2Je+DAAX75y1/y17/+lZEjR/o7zoCQnZ3N5s2bmT59ervriIvuO3r0KLfddhuPPvooP/nJT/wdp1PvvvsuVVVVLFy4kNDQUFQqVb/+LHj11Ve9f54/fz6LFy/GZDL12usP6qJw7bXX8sADD/DWW2/hdrvJzc31d6QOLV++HIfDwRNPPAGAwWDgmWee8XOqwPb/27ufUPjWOI7j7/G3pGGFZMxihmRBsZgsbSYWmoUkyQbZKvk3SFaaiVKmjJoVssAGs2KhKAtsbJRmQSYy/iQmdiN3ofuUfm7jXtfV7/q8dqdz5umcmunTPM95vt/3+ojLv2N2dpZ4PM7MzIx5gSMUCn3Jwuhnud1uvF4vra2tJBIJhoaGfos1u6+iKqkiImL86FdSRUTkLYWCiIgYCgURETEUCiIiYigURETEUCiIJLG3t/ePi9DFYjG8Xq85Xl1dpbGxEY/HQ0NDA/Pz8+Zcf38/V1dXn75fkc9QKIh8ofHxcTo7OwFYWlpibm6OYDDI2toai4uLrK+vs7KyAkBXV5f2Ssi3+9Gb10T+jtPTU0ZHR7m/vycrK4vh4WEqKiqIxWL09vby8PBAaWkpBwcH7OzsEI1Gub6+xuFwABAMBhkfHycvLw8Aq9WK3+/n8fERAKfTycXFBdFolOLi4m97TvnZ9E9B5IP6+vpoa2sjHA7j9Xrp7u42u8zr6+sJh8PU1dWZKaCtrS2qqqoAuLu74/LykvLy8jdjOhwOKisrzXF1dbUp5SzyHRQKIh/w9PRENBrF7XYDr6W2c3JyODk5YXd3F4/HA7yWzrBarQCcnZ1RUFAAQErK608tWfmEwsLC36LZj/x/KRREPuC9ajAvLy88Pz+Tmpr67nmLxWLKcOfm5mKz2X7p2bC/v8/k5KQ5TktLMwEi8h307RP5gOzsbIqKitjc3ATg8PCQ29tbSkpKqKmpIRwOA7C9vU08Hgdem+JcXFyYMTo6OvD5fNzc3ACvU0o+nw+73W6uOT8/13qCfCstNIt80MTEBGNjYwQCAdLT0wkEAmRkZDA8PMzAwADLy8uUlZWZ6aPa2lp6e3vN51taWkgkErS3t2OxWHh5eaG5uZmmpiZzzcHBAVNTU//5s4n8SaEgkoTL5cLlcgGwsLDwy/mNjQ1GRkZwOp0cHR0RiUQAsNvt5OfnE4lETK+Gtra2v9zzcHx8TGFhITab7YueRCQ5hYLIJ9ntdnp6ekhJSSEzM/NNk3qv18v09DR+vz/pOKFQiMHBwa+8VZGk1E9BREQMLTSLiIihUBAREUOhICIihkJBREQMhYKIiBgKBRERMf4AlFxMIZoF1GwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xf0dd710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot CV误差曲线\n",
    "test_means = grid_svc.cv_results_[ 'mean_test_score' ]\n",
    "test_stds = grid_svc.cv_results_[ 'std_test_score' ]\n",
    "train_means = grid_svc.cv_results_[ 'mean_train_score' ]\n",
    "train_stds = grid_svc.cv_results_[ 'std_train_score' ]\n",
    "\n",
    "\n",
    "# plot results\n",
    "n_Cs = len(tuned_parameters_svc['C'])\n",
    "number_penaltys = len(tuned_parameters_svc['penalty'])\n",
    "test_scores = np.array(test_means).reshape(n_Cs,number_penaltys)\n",
    "train_scores = np.array(train_means).reshape(n_Cs,number_penaltys)\n",
    "test_stds = np.array(test_stds).reshape(n_Cs,number_penaltys)\n",
    "train_stds = np.array(train_stds).reshape(n_Cs,number_penaltys)\n",
    "x_axis = np.log10(tuned_parameters_svc['C'])\n",
    "\n",
    "for i, value in enumerate(tuned_parameters_svc['penalty']):\n",
    "    #pyplot.plot(log(Cs), test_scores[i], label= 'penalty:'   + str(value))\n",
    "    plt.errorbar(x_axis, test_scores[:,i] ,label = tuned_parameters_svc['penalty'][i] +' Test')\n",
    "    plt.errorbar(x_axis, train_scores[:,i] ,label = tuned_parameters_svc['penalty'][i] +' Train')\n",
    "\n",
    "\n",
    "plt.legend()\n",
    "plt.xlabel( 'log(C)' )                                                                                                      \n",
    "plt.ylabel( 'accuracy' )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xf3597f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x_axis, test_scores[:,:], 'b-')\n",
    "plt.xlabel( 'log(C)' )                                                                                                      \n",
    "plt.ylabel( 'accuracy' )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "随着C值变化，训练模型和测试模型的得分变化图。可以看出线性SVM 的训练结果的准确率是要优于 logistic 回归的。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "网上找的的相关资料\n",
    "\n",
    "如何选择\n",
    "\n",
    "既然SVM与Logistic非常相似，那是不是它们可以混合使用呢？结果是否定的，在不同的情况下，应该选择不同的算法。\n",
    "用n表示Feature数量，m表示训练集个数。下面分情况讨论\n",
    "\n",
    "n很大，m很小\n",
    "n很大，一般指n=10000；m很小，一般m=10-1000。m很小，说明没有足够的训练集来拟合非常复杂的非线性模型，所以这种情况既可以选择线性kernel的SVM，也可以选择Logistic回归。\n",
    "\n",
    "n很小，m中等\n",
    "n很小，一般指n=1-1000；m很小，一般m=1000-10000。m中等，说明有足够的训练集来拟合非常复杂的非线性模型，此时适合选择非线性kernel的SVM，比如高斯核kernel的SVM。\n",
    "\n",
    "n很小，m很大\n",
    "n很小，一般指n=1-1000；m很大，一般m=50000-1000000。m很大，说明有足够的训练集来拟合非常复杂的非线性模型，但m很大的情况下，带核函数的SVM计算也非常慢。所以此时应该选线性kernel的SVM，也可以选择Logistic回归。n很小，说明Feature可能不足以表达模型，所以要添加更多Feature。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "logsitic 回归速度是要快于 linearSVC 的"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 9 核化SVM "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 9.1 模型训练及最优值寻找"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.svm import SVC\n",
    "# 定义优化参数字典\n",
    "tuned_parameters_ksvc ={'C':[0.001,0.005,0.01,0.05,0.1,0.5,1,5,10,20,30,100], 'gamma': [100,50,10,5,1,0.5,0.3,0.1,0.05,0.03,0.01,0.001,0.0001]}\n",
    "ksvc =SVC(tol=1e-6,kernel='rbf',class_weight=\"balanced\", random_state=20)\n",
    "grid_ksvc=GridSearchCV(ksvc,tuned_parameters_ksvc)\n",
    "# 训练数据\n",
    "grid_ksvc.fit(x_train,y_train)\n",
    "ksvc_predict_test =grid_ksvc.predict(x_test)\n",
    "ksvc_predict_train =grid_ksvc.predict(x_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 9.2 结果评分及图像绘制"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('best params for kernal svm: ', {'C': 1, 'gamma': 0.03})\n",
      "('best score for kernal svm: ', 0.8420195439739414)\n",
      "confusion matrix:\n",
      "[[47 13]\n",
      " [16 78]]\n",
      "regression report:\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          1    0.74603   0.78333   0.76423        60\n",
      "          0    0.85714   0.82979   0.84324        94\n",
      "\n",
      "avg / total    0.81385   0.81169   0.81246       154\n",
      "\n",
      "accuracy score for train data: 0.85016\n",
      "accuracy score for test data: 0.81169\n"
     ]
    }
   ],
   "source": [
    "print(\"best params for kernal svm: \",grid_ksvc.best_params_)\n",
    "print(\"best score for kernal svm: \",grid_ksvc.best_score_)\n",
    "print(\"confusion matrix:\")\n",
    "print(metrics.confusion_matrix(y_test, ksvc_predict_test, labels=[1, 0]) )\n",
    "print(\"regression report:\")\n",
    "print(metrics.classification_report(y_test, ksvc_predict_test, labels=[1,0], digits=5))\n",
    "print(\"accuracy score for train data: {0:.5f}\".format(metrics.accuracy_score(y_train, ksvc_predict_train)))\n",
    "print(\"accuracy score for test data: {0:.5f}\".format(metrics.accuracy_score(y_test, ksvc_predict_test)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "根据不断尝试 调整 C 和 gamma 可以找到  C =1 gamma =0.03 的时候得到最优解，在训练集上准确率达到0.85 ,在测试集上面准确率达到0.81"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fit_grid_point_RBF(C, gamma, x_train, y_train, x_val, y_val):\n",
    "    \n",
    "    # 在训练集是那个利用SVC训练\n",
    "    SVC3 =  SVC( C = C, kernel='rbf', class_weight=\"balanced\",gamma = gamma)\n",
    "    SVC3 = SVC3.fit(x_train, y_train)\n",
    "    \n",
    "    # 在校验集上返回accuracy\n",
    "    accuracy = SVC3.score(x_val, y_val)\n",
    "    \n",
    "    return accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xf2bd390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#需要调优的参数\n",
    "C_s = [0.1,0.5,1,5,10]# logspace(a,b,N)把10的a次方到10的b次方区间分成N份 \n",
    "gamma_s = [0.03]  \n",
    "\n",
    "accuracy_s = []\n",
    "for i, oneC in enumerate(C_s):\n",
    "    for j, gamma in enumerate(gamma_s):\n",
    "        tmp = fit_grid_point_RBF(oneC, gamma, x_train, y_train, x_test, y_test)\n",
    "        accuracy_s.append(tmp)\n",
    "        \n",
    "accuracy_s1 =np.array(accuracy_s).reshape(len(C_s),len(gamma_s))\n",
    "x_axis = np.log10(C_s)\n",
    "for j, gamma in enumerate(gamma_s):\n",
    "    plt.plot(x_axis, np.array(accuracy_s1[:,j]), label = ' Test - log(gamma)' + str(np.log10(gamma)))\n",
    "\n",
    "plt.legend()\n",
    "plt.xlabel( 'log(C)' )                                                                                                      \n",
    "plt.ylabel( 'accuracy' )\n",
    "plt.savefig('RBF_SVM_Otto.png' )\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "确定 gamma 的情况下，准确率随 C值变化情况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
